fix SSE cleanup, filter add popover to completed only, derive isGenerating from pending set, handle not_found status

Generations now return immediately with a 'generating' status and appear
in history right away. TTS runs in a serial background queue to avoid
GPU contention. Users can kick off multiple generations without blocking.

- Async POST /generate creates DB record immediately, queues TTS work
- Serial generation queue prevents concurrent GPU access (Metal/CUDA/CPU)
- SSE endpoint GET /generate/{id}/status for real-time completion tracking
- Retry endpoint POST /generate/{id}/retry for failed generations
- Store engine and model_size on generation records for retry support
- History cards show animated loader (react-loaders) for generating/playing
- Failed generations show retry button instead of actions menu
- Model downloads happen inline in the queue instead of rejecting with 202
- Stale 'generating' records marked as failed on server startup
- Autoplay on generate setting (default: on)
- Show engine name on generation cards
- Remove sidebar generation spinner
- Checkbox alignment fix in settings

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.11
+current_version = 0.1.13
 commit = True
 tag = True
 tag_name = v{new_version}

.dockerignore

@@ -0,0 +1,46 @@
+# Version control
+.git
+.github
+.gitignore
+
+# Desktop-only (not needed in web container)
+tauri/
+landing/
+docs/
+mlx-test/
+scripts/
+
+# Dependencies & build artifacts (rebuilt in Docker)
+node_modules/
+__pycache__/
+*.pyc
+*.pyo
+*.egg-info/
+dist/
+build/
+*.spec
+
+# Data (will be bind-mounted)
+data/
+backend/data/
+
+# IDE & OS
+.vscode/
+.idea/
+*.swp
+*.swo
+.DS_Store
+Thumbs.db
+
+# Config files not needed in container
+biome.json
+.biomeignore
+.bumpversion.cfg
+.npmrc
+Makefile
+CHANGELOG.md
+CONTRIBUTING.md
+SECURITY.md
+LICENSE
+README.md
+backend/README.md

.github/workflows/build-cuda.yml

@@ -0,0 +1,73 @@
+name: Build CUDA Backend
+
+on:
+  workflow_dispatch:
+  push:
+    tags:
+      - "v*"
+
+jobs:
+  build-cuda-windows:
+    runs-on: windows-latest
+    permissions:
+      contents: write
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+          cache: "pip"
+
+      - name: Install Python dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install pyinstaller
+          pip install -r backend/requirements.txt
+
+      - name: Install PyTorch with CUDA 12.1
+        run: |
+          pip install torch --index-url https://download.pytorch.org/whl/cu121 --force-reinstall --no-deps
+          pip install torchaudio --index-url https://download.pytorch.org/whl/cu121
+
+      - name: Verify CUDA support in torch
+        run: |
+          python -c "import torch; print(f'CUDA available in build: {torch.cuda.is_available()}'); print(f'CUDA version: {torch.version.cuda}')"
+
+      - name: Build CUDA server binary
+        shell: bash
+        working-directory: backend
+        run: python build_binary.py --cuda
+
+      - name: Split binary for GitHub Releases
+        shell: bash
+        run: |
+          python scripts/split_binary.py \
+            backend/dist/voicebox-server-cuda.exe \
+            --output release-assets/
+
+      - name: Upload split parts to GitHub Release
+        if: startsWith(github.ref, 'refs/tags/')
+        uses: softprops/action-gh-release@v1
+        with:
+          files: |
+            release-assets/voicebox-server-cuda.part*.exe
+            release-assets/voicebox-server-cuda.sha256
+            release-assets/voicebox-server-cuda.manifest
+          draft: true
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Upload binary as workflow artifact (for testing)
+        uses: actions/upload-artifact@v4
+        with:
+          name: voicebox-server-cuda-windows
+          path: backend/dist/voicebox-server-cuda.exe
+          retention-days: 7
+
+  # Linux CUDA build can be added later with:
+  # build-cuda-linux:
+  #   runs-on: ubuntu-22.04
+  #   ...

.github/workflows/build-windows.yml

@@ -0,0 +1,63 @@
+name: Build Windows
+
+on:
+  workflow_dispatch:
+
+jobs:
+  build-windows:
+    permissions:
+      contents: write
+    runs-on: windows-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+          cache: "pip"
+
+      - name: Install Python dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install pyinstaller
+          pip install -r backend/requirements.txt
+
+      - name: Build Python server
+        shell: bash
+        run: |
+          cd backend
+          python build_binary.py
+
+          PLATFORM=$(rustc --print host-tuple)
+          mkdir -p ../tauri/src-tauri/binaries
+          cp dist/voicebox-server.exe ../tauri/src-tauri/binaries/voicebox-server-${PLATFORM}.exe
+          echo "Built voicebox-server-${PLATFORM}.exe"
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@v2
+
+      - name: Install Rust stable
+        uses: dtolnay/rust-toolchain@stable
+
+      - name: Rust cache
+        uses: swatinem/rust-cache@v2
+        with:
+          workspaces: "./tauri/src-tauri -> target"
+
+      - name: Install dependencies
+        run: bun install
+
+      - uses: tauri-apps/tauri-action@v0
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          projectPath: tauri
+          tagName: v__VERSION__
+          releaseName: "voicebox v__VERSION__ (test build)"
+          releaseBody: "Test build for audio export fix"
+          releaseDraft: true
+          prerelease: true
+          args: ""
+          includeUpdaterJson: false

.github/workflows/release.yml

@@ -4,7 +4,7 @@ on:
   workflow_dispatch:
   push:
     tags:
-      - 'v*'
+      - "v*"
 
 jobs:
   release:
@@ -14,22 +14,22 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - platform: 'macos-latest'
+          - platform: "macos-latest"
-            args: '--target aarch64-apple-darwin'
+            args: "--target aarch64-apple-darwin"
-            python-version: '3.12'
+            python-version: "3.12"
-            backend: 'mlx'
+            backend: "mlx"
-          - platform: 'macos-15-intel'
+          - platform: "macos-15-intel"
-            args: '--target x86_64-apple-darwin'
+            args: "--target x86_64-apple-darwin"
-            python-version: '3.12'
+            python-version: "3.12"
-            backend: 'pytorch'
+            backend: "pytorch"
-          # - platform: 'ubuntu-22.04'
+          - platform: "ubuntu-22.04"
-          #   args: ''
+            args: ""
-          #   python-version: '3.12'
+            python-version: "3.12"
-          #   backend: 'pytorch'
+            backend: "pytorch"
-          - platform: 'windows-latest'
+          - platform: "windows-latest"
-            args: ''
+            args: ""
-            python-version: '3.12'
+            python-version: "3.12"
-            backend: 'pytorch'
+            backend: "pytorch"
 
     runs-on: ${{ matrix.platform }}
 
@@ -53,7 +53,7 @@ jobs:
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
-          cache: 'pip'
+          cache: "pip"
 
       - name: Install Python dependencies
         run: |
@@ -66,6 +66,12 @@ jobs:
         run: |
           pip install -r backend/requirements-mlx.txt
 
+      # - name: Install PyTorch with CUDA (Windows only)
+      #   if: matrix.platform == 'windows-latest'
+      #   run: |
+      #     pip install torch --index-url https://download.pytorch.org/whl/cu121 --force-reinstall --no-deps
+      #     pip install torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
+
       - name: Build Python server (Linux/macOS)
         if: matrix.platform != 'windows-latest'
         run: |
@@ -100,7 +106,7 @@ 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
@@ -136,7 +142,7 @@ 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.

CHANGELOG.md

@@ -5,6 +5,14 @@ All notable changes to Voicebox will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Fixed
+- **Profile Name Validation** - Added proper validation to prevent duplicate profile names ([#134](https://github.com/jamiepine/voicebox/issues/134))
+  - Users now receive clear error messages when attempting to create or update profiles with duplicate names
+  - Improved error handling in create and update profile API endpoints
+  - Added comprehensive test suite for duplicate name validation
+
 ## [0.1.0] - 2026-01-25
 
 ### Added
@@ -53,6 +61,10 @@ 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
+- OpenAPI client generator script now documents the local backend port and avoids an unused loop variable warning
+
 ### Added
 - **Makefile** - Comprehensive development workflow automation with commands for setup, development, building, testing, and code quality checks
   - Includes Python version detection and compatibility warnings

CONTRIBUTING.md

@@ -27,12 +27,32 @@ Thank you for your interest in contributing to Voicebox! This document provides
   ```bash
   rustc --version  # Check if installed
   ```
+- **[Tauri Prerequisites](https://v2.tauri.app/start/prerequisites)** - Tauri-specific system dependencies (varies by OS).
 
 - **Git** - Version control
 
 ### Development Setup
 
-**Using the Makefile (recommended for macOS/Linux):** Run `make setup` to install all dependencies, then `make dev` to start development servers. See `make help` for all available commands.
+**Using `just` (recommended):**
+
+Install [just](https://github.com/casey/just) (`brew install just` or `cargo install just`), then:
+
+```bash
+just setup   # creates venv, installs Python + JS deps
+just dev     # starts backend + desktop app in one terminal
+```
+
+Other useful commands:
+
+```bash
+just dev-web       # backend + web app (no Tauri/Rust build)
+just dev-backend   # backend only
+just kill          # stop all dev processes
+just clean-all     # nuke everything and start fresh
+just --list        # see all available commands
+```
+
+**Using the Makefile:** Run `make setup` then `make dev`. See `make help` for all commands.
 
 **Manual setup (required for Windows):**
 
@@ -407,7 +427,7 @@ See [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md) for common issues and sol
 
 - **Backend won't start:** Check Python version (3.11+), ensure venv is activated, install dependencies
 - **Tauri build fails:** Ensure Rust is installed, clean build with `cd tauri/src-tauri && cargo clean`
-- **OpenAPI client generation fails:** Ensure backend is running, check `curl http://localhost:8000/openapi.json`
+- **OpenAPI client generation fails:** Ensure backend is running, check `curl http://localhost:17493/openapi.json`
 
 ## Questions?
 

Dockerfile

@@ -0,0 +1,79 @@
+# ============================================================
+# Voicebox — Local TTS Server with Web UI (CPU)
+# 3-stage build: Frontend → Python deps → Runtime
+# ============================================================
+
+# === Stage 1: Build frontend ===
+FROM oven/bun:1 AS frontend
+
+WORKDIR /build
+
+# Copy workspace config and frontend source
+COPY package.json bun.lock ./
+COPY app/ ./app/
+COPY web/ ./web/
+
+# Strip workspaces not needed for web build, and fix trailing comma
+RUN sed -i '/"tauri"/d; /"landing"/d' package.json && \
+    sed -i -z 's/,\n  ]/\n  ]/' package.json
+RUN bun install --no-save
+# Build frontend (skip tsc — upstream has pre-existing type errors)
+RUN cd web && bunx --bun vite build
+
+
+# === Stage 2: Build Python dependencies ===
+FROM python:3.11-slim AS backend-builder
+
+WORKDIR /build
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    git \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY backend/requirements.txt .
+RUN pip install --no-cache-dir --prefix=/install -r requirements.txt
+RUN pip install --no-cache-dir --prefix=/install \
+    git+https://github.com/QwenLM/Qwen3-TTS.git
+
+
+# === Stage 3: Runtime ===
+FROM python:3.11-slim
+
+# Create non-root user for security
+RUN groupadd -r voicebox && \
+    useradd -r -g voicebox -m -s /bin/bash voicebox
+
+WORKDIR /app
+
+# Install only runtime system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ffmpeg \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy installed Python packages from builder stage
+COPY --from=backend-builder /install /usr/local
+
+# Copy backend application code
+COPY --chown=voicebox:voicebox backend/ /app/backend/
+
+# Copy built frontend from frontend stage
+COPY --from=frontend --chown=voicebox:voicebox /build/web/dist /app/frontend/
+
+# Create data directories owned by non-root user
+RUN mkdir -p /app/data/generations /app/data/profiles /app/data/cache \
+    && chown -R voicebox:voicebox /app/data
+
+# Switch to non-root user
+USER voicebox
+
+# Expose the API port
+EXPOSE 17493
+
+# Health check — auto-restart if the server hangs
+HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=60s \
+    CMD curl -f http://localhost:17493/health || exit 1
+
+# Start the FastAPI server
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "17493"]

Makefile

@@ -48,6 +48,7 @@ setup-python: $(VENV)/bin/activate ## Set up Python virtual environment and depe
 	@echo -e "$(BLUE)Installing Python dependencies...$(NC)"
 	$(PIP) install --upgrade pip
 	$(PIP) install -r $(BACKEND_DIR)/requirements.txt
+	$(PIP) install --no-deps chatterbox-tts
 	@if [ "$$(uname -m)" = "arm64" ] && [ "$$(uname)" = "Darwin" ]; then \
 		echo -e "$(BLUE)Detected Apple Silicon - installing MLX dependencies...$(NC)"; \
 		$(PIP) install -r $(BACKEND_DIR)/requirements-mlx.txt; \
@@ -79,7 +80,11 @@ dev: ## Start backend + desktop app (parallel)
 	@echo -e "$(YELLOW)Note: If Tauri fails, run 'make build-server' first or use separate terminals$(NC)"
 	@trap 'kill 0' EXIT; \
 		$(MAKE) dev-backend & \
-		sleep 2 && $(MAKE) dev-frontend & \
+		sleep 2 && if [ "$$(uname)" = "Linux" ] && lspci 2>/dev/null | grep -qi nvidia; then \
+			WEBKIT_DISABLE_DMABUF_RENDERER=1 $(MAKE) dev-frontend; \
+		else \
+			$(MAKE) dev-frontend; \
+		fi & \
 		wait
 
 dev-backend: ## Start FastAPI backend server

PATCH_NOTES.md

@@ -0,0 +1,58 @@
+# Voicebox Offline Mode Fix
+
+## Problem
+Voicebox crashes when generating speech if HuggingFace is unreachable, even when models are fully cached locally.
+
+**Root Cause:**
+- Voicebox downloads `mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16` (MLX optimized version)
+- But `mlx_audio.tts.load()` tries to fetch `config.json` from original repo `Qwen/Qwen3-TTS-12Hz-1.7B-Base`
+- This network request fails → server crashes with `RemoteDisconnected`
+
+**Related Issues:**
+- Issue #150: "Internet connection required, even though models are downloaded?"
+- Issue #151: "API Stability Issues: Model Loading Hangs and Server Crashes"
+
+## Solution
+Two-part fix:
+
+### 1. Monkey-patch huggingface_hub (`backend/utils/hf_offline_patch.py`)
+- Intercepts cache lookup functions
+- Forces offline mode early (before mlx_audio imports)
+- Adds debug logging for cache hits/misses
+
+### 2. Symlink original repo to MLX version (`ensure_original_qwen_config_cached()`)
+- When original `Qwen/Qwen3-TTS-12Hz-1.7B-Base` cache doesn't exist
+- But MLX `mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16` does exist
+- Creates a symlink so cache lookups succeed
+
+## Files Changed
+- `backend/backends/mlx_backend.py` - Added patch imports at top
+- `backend/utils/hf_offline_patch.py` - New patch module
+
+## Testing
+To test this fix:
+1. Build Voicebox from source: `make build`
+2. Disconnect from internet
+3. Try generating speech
+4. Should work without network requests
+
+## Build Instructions
+
+```bash
+# Install dependencies
+pip install -r requirements.txt
+
+# Build the app
+make build
+
+# Or build just the server
+make build-server
+```
+
+## Notes
+- The patch is applied automatically when `mlx_backend.py` is imported
+- Set `VOICEBOX_OFFLINE_PATCH=0` to disable the patch
+- The symlink approach works because the config.json is compatible between versions
+
+---
+*Patch contributed by community*

README.md

@@ -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:
 
@@ -80,10 +80,10 @@ Voicebox is available now for macOS and Windows.
 
 | 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 (Apple Silicon) | [Voicebox_aarch64.app.tar.gz](https://github.com/jamiepine/voicebox/releases/latest/download/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) |
+| macOS (Intel) | [Voicebox_x64.app.tar.gz](https://github.com/jamiepine/voicebox/releases/latest/download/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 (MSI) | [Latest Windows MSI](https://github.com/jamiepine/voicebox/releases/latest) |
-| 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) |
+| Windows (Setup) | [Latest Windows Setup](https://github.com/jamiepine/voicebox/releases/latest) |
 
 > **Linux builds coming soon** — Currently blocked by GitHub runner disk space limitations.
 
@@ -98,12 +98,12 @@ 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
+- **Lightning fast on Mac** — MLX backend leverages Apple Silicon's Neural Engine for super-fast generation
 
 ### Voice Profile Management
 
 - **Create profiles** from audio files or record directly in-app
-- **Import/Export** profiles to share or backup
+- **Import/Export** profiles to share or back up
 - **Multi-sample support** — combine multiple samples for higher quality cloning
 - **Organize** with descriptions and language tags
 
@@ -147,17 +147,20 @@ Create multi-voice narratives, podcasts, and conversations with a timeline-based
 
 Voicebox exposes a full REST API, so you can integrate voice synthesis into your own apps.
 
+For the current local app and development workflow, the backend is typically available at `http://localhost:17493`.
+If you launch the backend manually with a different host or port, use that address instead.
+
 ```bash
 # Generate speech
-curl -X POST http://localhost:8000/generate \
+curl -X POST http://localhost:17493/generate \
   -H "Content-Type: application/json" \
   -d '{"text": "Hello world", "profile_id": "abc123", "language": "en"}'
 
 # List voice profiles
-curl http://localhost:8000/profiles
+curl http://localhost:17493/profiles
 
 # Create a profile
-curl -X POST http://localhost:8000/profiles \
+curl -X POST http://localhost:17493/profiles \
   -H "Content-Type: application/json" \
   -d '{"name": "My Voice", "language": "en"}'
 ```
@@ -170,7 +173,7 @@ curl -X POST http://localhost:8000/profiles \
 - Voice assistants
 - Content creation automation
 
-Full API documentation available at `http://localhost:8000/docs` when running.
+Full API documentation is available at `http://localhost:17493/docs` in the default local workflow, or at `/docs` on whatever server address you configured.
 
 ---
 
@@ -225,42 +228,21 @@ Voicebox aims to be the **one-stop shop for everything voice** — cloning, synt
 
 See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed setup and contribution guidelines.
 
-**Using the Makefile (recommended):** Run `make help` to see all available commands for setup, development, building, and testing.
-
 ### Quick Start
 
-**With Makefile (Unix/macOS/Linux):**
-
 ```bash
-# Clone the repo
+git clone https://github.com/jamiepine/voicebox.git
-git clone https://github.com/voicebox-sh/voicebox.git
 cd voicebox
 
-# Setup everything
+just setup   # creates Python venv, installs all deps
-make setup
+just dev     # starts backend + desktop app
-
-# Start development
-make dev
 ```
 
-**Manual setup (all platforms):**
+Install [just](https://github.com/casey/just): `brew install just` or `cargo install just`. Run `just --list` to see all commands.
 
-```bash
+Also available via Makefile: `make setup && make dev` (run `make help` for all commands).
-# Clone the repo
-git clone https://github.com/voicebox-sh/voicebox.git
-cd voicebox
 
-# Install dependencies
+**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org), [XCode on macOS](https://developer.apple.com/xcode/), [Tauri Prerequisites](https://v2.tauri.app/start/prerequisites/).
-bun install
-
-# Install Python dependencies
-cd backend && pip install -r requirements.txt && cd ..
-
-# Start development
-bun run dev
-```
-
-**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org). 
 
 **Performance:** 
 - **Apple Silicon (M1/M2/M3)**: Uses MLX backend with native Metal acceleration for 4-5x faster inference

app/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@voicebox/app",
-  "version": "0.1.11",
+  "version": "0.1.13",
   "private": true,
   "type": "module",
   "scripts": {

app/src/App.tsx

@@ -1,13 +1,14 @@
-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 { cn } from '@/lib/utils/cn';
+import { usePlatform } from '@/platform/PlatformContext';
 import { router } from '@/router';
 import { useServerStore } from '@/stores/serverStore';
-import { usePlatform } from '@/platform/PlatformContext';
 
 const LOADING_MESSAGES = [
   'Warming up tensors...',
@@ -38,6 +39,9 @@ function App() {
   const [loadingMessageIndex, setLoadingMessageIndex] = useState(0);
   const serverStartingRef = useRef(false);
 
+  // Automatically check for app updates on startup and show toast notifications
+  useAutoUpdater({ checkOnMount: true, showToast: true });
+
   // Sync stored setting to Rust on startup
   useEffect(() => {
     if (platform.metadata.isTauri) {
@@ -46,14 +50,18 @@ function App() {
         console.error('Failed to sync initial setting to Rust:', error);
       });
     }
-  }, [platform]);
+    // 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);
     };
-  }, [platform]);
+    // 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(() => {
@@ -85,10 +93,12 @@ function App() {
     }
 
     serverStartingRef.current = true;
-    console.log('Production mode: Starting bundled server...');
+    const isRemote = useServerStore.getState().mode === 'remote';
+    const customModelsDir = useServerStore.getState().customModelsDir;
+    console.log(`Production mode: Starting bundled server... (remote: ${isRemote})`);
 
     platform.lifecycle
-      .startServer(false)
+      .startServer(isRemote, customModelsDir)
       .then((serverUrl) => {
         console.log('Server is ready at:', serverUrl);
         // Update the server URL in the store with the dynamically assigned port
@@ -111,7 +121,9 @@ function App() {
       // Window close event handles server shutdown based on setting
       serverStartingRef.current = false;
     };
-  }, [platform]);
+    // 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(() => {

app/src/components/AudioPlayer/AudioPlayer.tsx

@@ -1,17 +1,18 @@
 import { useQuery } from '@tanstack/react-query';
 import { Pause, Play, Repeat, Volume2, VolumeX, X } from 'lucide-react';
-import { useEffect, useMemo, useRef, useState } from 'react';
+import { useEffect, useId, 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 { formatAudioDuration } from '@/lib/utils/audio';
 import { debug } from '@/lib/utils/debug';
-import { usePlayerStore } from '@/stores/playerStore';
 import { usePlatform } from '@/platform/PlatformContext';
+import { usePlayerStore } from '@/stores/playerStore';
 
 export function AudioPlayer() {
   const platform = usePlatform();
+  const volumeLabelId = useId();
   const {
     audioUrl,
     audioId,
@@ -359,7 +360,7 @@ export function AudioPlayer() {
         if (shouldAutoPlayNow) {
           // Clear the flag first
           usePlayerStore.getState().clearAutoPlayFlag();
-          
+
           // Use a small delay to ensure audio element is fully ready
           setTimeout(() => {
             wavesurfer.play().catch((error) => {
@@ -664,7 +665,7 @@ export function AudioPlayer() {
   // Handle shouldAutoPlay flag - for story mode auto-advance
   const shouldAutoPlay = usePlayerStore((state) => state.shouldAutoPlay);
   const clearAutoPlayFlag = usePlayerStore((state) => state.clearAutoPlayFlag);
-  
+
   useEffect(() => {
     const wavesurfer = wavesurferRef.current;
     if (!wavesurfer || !shouldAutoPlay || duration === 0) {
@@ -831,6 +832,9 @@ export function AudioPlayer() {
             disabled={isLoading || duration === 0}
             className="shrink-0"
             title={duration === 0 && !isLoading ? 'Audio not loaded' : ''}
+            aria-label={
+              duration === 0 && !isLoading ? 'Audio not loaded' : isPlaying ? 'Pause' : 'Play'
+            }
           >
             {isPlaying ? <Pause className="h-5 w-5" /> : <Play className="h-5 w-5" />}
           </Button>
@@ -845,6 +849,8 @@ export function AudioPlayer() {
                 max={100}
                 step={0.1}
                 className="w-full"
+                aria-label="Playback position"
+                aria-valuetext={`${formatAudioDuration(currentTime)} of ${formatAudioDuration(duration)}`}
               />
             )}
             {isLoading && (
@@ -862,7 +868,9 @@ export function AudioPlayer() {
 
           {/* Title */}
           {title && (
-            <div className="text-sm font-medium truncate max-w-[200px] shrink-0">{title}</div>
+            <div className="text-sm font-medium truncate max-w-[200px] shrink-0 hidden lg:block">
+              {title}
+            </div>
           )}
 
           {/* Loop Button */}
@@ -872,26 +880,37 @@ export function AudioPlayer() {
             onClick={toggleLoop}
             className={isLooping ? 'text-primary' : ''}
             title="Toggle loop"
+            aria-label={isLooping ? 'Stop looping' : 'Loop'}
           >
             <Repeat className="h-4 w-4" />
           </Button>
 
           {/* Volume Control */}
-          <div className="flex items-center gap-2 shrink-0 w-[120px]">
+          <div
+            className="flex items-center gap-2 shrink-0 w-[120px]"
+            role="group"
+            aria-label="Volume"
+          >
             <Button
               variant="ghost"
               size="icon"
               onClick={() => setVolume(volume > 0 ? 0 : 1)}
               className="h-8 w-8"
+              aria-label={volume > 0 ? 'Mute' : 'Unmute'}
             >
               {volume > 0 ? <Volume2 className="h-4 w-4" /> : <VolumeX className="h-4 w-4" />}
             </Button>
+            <span id={volumeLabelId} className="sr-only">
+              Volume level, {Math.round(volume * 100)}%
+            </span>
             <Slider
               value={[volume * 100]}
               onValueChange={handleVolumeChange}
               max={100}
               step={1}
               className="flex-1"
+              aria-labelledby={volumeLabelId}
+              aria-valuetext={`${Math.round(volume * 100)}%`}
             />
           </div>
 
@@ -902,6 +921,7 @@ export function AudioPlayer() {
             onClick={handleClose}
             className="shrink-0"
             title="Close player"
+            aria-label="Close player"
           >
             <X className="h-5 w-5" />
           </Button>

app/src/components/AudioTab/AudioTab.tsx

@@ -23,8 +23,8 @@ import {
 import { apiClient } from '@/lib/api/client';
 import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
 import { cn } from '@/lib/utils/cn';
-import { usePlayerStore } from '@/stores/playerStore';
 import { usePlatform } from '@/platform/PlatformContext';
+import { usePlayerStore } from '@/stores/playerStore';
 
 interface AudioDevice {
   id: string;
@@ -124,6 +124,13 @@ export function AudioTab() {
     );
   }
 
+  const handleChannelDelete = async (e, channelId) => {
+    e.stopPropagation();
+    if (await confirm('Delete this channel?')) {
+      deleteChannel.mutate(channelId);
+    }
+  };
+
   const allChannels = channels || [];
   const allDevices = devices || [];
   const selectedChannel = selectedChannelId
@@ -161,7 +168,7 @@ export function AudioTab() {
               </Button>
             </div>
           ) : (
-            <div className="space-y-3 p-2">
+            <div className="space-y-3">
               {allChannels.map((channel) => {
                 const isSelected = selectedChannelId === channel.id;
                 return (
@@ -241,12 +248,7 @@ export function AudioTab() {
                             variant="ghost"
                             size="sm"
                             className="h-8 w-8 p-0"
-                            onClick={(e) => {
+                            onClick={(e) => handleChannelDelete(e, channel.id)}
-                              e.stopPropagation();
-                              if (confirm('Delete this channel?')) {
-                                deleteChannel.mutate(channel.id);
-                              }
-                            }}
                           >
                             <Trash2 className="h-4 w-4" />
                           </Button>
@@ -341,7 +343,9 @@ export function AudioTab() {
             <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" />
               <p className="text-muted-foreground text-center">
-                {platform.metadata.isTauri ? 'No audio devices found' : 'Audio device selection requires Tauri'}
+                {platform.metadata.isTauri
+                  ? 'No audio devices found'
+                  : 'Audio device selection requires Tauri'}
               </p>
             </div>
           )}

app/src/components/Generation/FloatingGenerateBox.tsx

@@ -1,6 +1,6 @@
 import { useMatchRoute } from '@tanstack/react-router';
 import { AnimatePresence, motion } from 'framer-motion';
-import { Loader2, MessageSquare, Sparkles } from 'lucide-react';
+import { Loader2, SlidersHorizontal, 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';
@@ -12,14 +12,15 @@ import {
   SelectValue,
 } from '@/components/ui/select';
 import { Textarea } from '@/components/ui/textarea';
-import { useToast } from '@/components/ui/use-toast';
+import { getLanguageOptionsForEngine, type LanguageCode } from '@/lib/constants/languages';
-import { LANGUAGE_OPTIONS } from '@/lib/constants/languages';
 import { useGenerationForm } from '@/lib/hooks/useGenerationForm';
 import { useProfile, useProfiles } from '@/lib/hooks/useProfiles';
-import { useAddStoryItem, useStory } from '@/lib/hooks/useStories';
+import { useStory } from '@/lib/hooks/useStories';
 import { cn } from '@/lib/utils/cn';
+import { useGenerationStore } from '@/stores/generationStore';
 import { useStoryStore } from '@/stores/storyStore';
 import { useUIStore } from '@/stores/uiStore';
+import { ParalinguisticInput } from './ParalinguisticInput';
 
 interface FloatingGenerateBoxProps {
   isPlayerOpen?: boolean;
@@ -43,8 +44,7 @@ export function FloatingGenerateBox({
   const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
   const trackEditorHeight = useStoryStore((state) => state.trackEditorHeight);
   const { data: currentStory } = useStory(selectedStoryId);
-  const addStoryItem = useAddStoryItem();
+  const addPendingStoryAdd = useGenerationStore((s) => s.addPendingStoryAdd);
-  const { toast } = useToast();
 
   // Calculate if track editor is visible (on stories route with items)
   const hasTrackEditor = isStoriesRoute && currentStory && currentStory.items.length > 0;
@@ -52,25 +52,9 @@ export function FloatingGenerateBox({
   const { form, handleSubmit, isPending } = useGenerationForm({
     onSuccess: async (generationId) => {
       setIsExpanded(false);
-      // If on stories route and a story is selected, add generation to story
+      // Defer the story add until TTS completes — useGenerationProgress handles it
       if (isStoriesRoute && selectedStoryId && generationId) {
-        try {
+        addPendingStoryAdd(generationId, selectedStoryId);
-          await addStoryItem.mutateAsync({
-            storyId: selectedStoryId,
-            data: { generation_id: generationId },
-          });
-          toast({
-            title: 'Added to story',
-            description: `Generation added to "${currentStory?.name || 'story'}"`,
-          });
-        } catch (error) {
-          toast({
-            title: 'Failed to add to story',
-            description:
-              error instanceof Error ? error.message : 'Could not add generation to story',
-            variant: 'destructive',
-          });
-        }
       }
     },
   });
@@ -112,6 +96,13 @@ export function FloatingGenerateBox({
     }
   }, [selectedProfileId, profiles, setSelectedProfileId]);
 
+  // Sync generation form language with selected profile's language
+  useEffect(() => {
+    if (selectedProfile?.language) {
+      form.setValue('language', selectedProfile.language as LanguageCode);
+    }
+  }, [selectedProfile, form]);
+
   // Auto-resize textarea based on content (only when expanded)
   useEffect(() => {
     if (!isExpanded) {
@@ -174,7 +165,7 @@ export function FloatingGenerateBox({
         isStoriesRoute
           ? // Position aligned with story list: after sidebar + padding, width 360px
             'left-[calc(5rem+2rem)] w-[360px]'
-          : 'left-[calc(5rem+2rem)] w-[calc((100%-5rem-4rem)/2-1rem)]',
+          : 'left-[calc(5rem+2rem)] right-8 lg:right-auto lg:w-[calc((100%-5rem-4rem)/2-1rem)]',
       )}
       style={{
         // On stories route: offset by track editor height when visible
@@ -187,7 +178,7 @@ 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}>
@@ -212,34 +203,57 @@ export function FloatingGenerateBox({
                             transition={{ duration: 0.15, ease: 'easeOut' }}
                             style={{ overflow: 'hidden' }}
                           >
-                            <Textarea
+                            {form.watch('engine') === 'chatterbox_turbo' ? (
-                              {...field}
+                              <ParalinguisticInput
-                              ref={(node: HTMLTextAreaElement | null) => {
+                                value={field.value}
-                                // Store ref for auto-resize (only for active field)
+                                onChange={field.onChange}
-                                if (!isInstructMode) {
+                                placeholder={
-                                  textareaRef.current = node;
+                                  isStoriesRoute && currentStory
+                                    ? `Generate speech for "${currentStory.name}"... (type / for effects)`
+                                    : selectedProfile
+                                      ? `Type / for effects like [laugh], [sigh]...`
+                                      : 'Select a voice profile above...'
                                 }
-                                // Forward ref to react-hook-form
+                                className="px-3 py-2 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 w-full"
-                                if (typeof field.ref === 'function') {
+                                style={{
-                                  field.ref(node);
+                                  minHeight: isExpanded ? '100px' : '32px',
+                                  maxHeight: '300px',
+                                  overflowY: 'auto',
+                                }}
+                                disabled={!selectedProfileId}
+                                onClick={() => setIsExpanded(true)}
+                                onFocus={() => setIsExpanded(true)}
+                              />
+                            ) : (
+                              <Textarea
+                                {...field}
+                                ref={(node: HTMLTextAreaElement | null) => {
+                                  // Store ref for auto-resize (only for active field)
+                                  if (!isInstructMode) {
+                                    textareaRef.current = node;
+                                  }
+                                  // Forward ref to react-hook-form
+                                  if (typeof field.ref === 'function') {
+                                    field.ref(node);
+                                  }
+                                }}
+                                placeholder={
+                                  isStoriesRoute && currentStory
+                                    ? `Generate speech for "${currentStory.name}"...`
+                                    : selectedProfile
+                                      ? `Generate speech using ${selectedProfile.name}...`
+                                      : 'Select a voice profile above...'
                                 }
-                              }}
+                                className="resize-none bg-transparent border-none focus-visible:ring-0 focus-visible:ring-offset-0 focus:outline-none focus:ring-0 outline-none ring-0 rounded-2xl text-sm placeholder:text-muted-foreground/60 w-full"
-                              placeholder={
+                                style={{
-                                isStoriesRoute && currentStory
+                                  minHeight: isExpanded ? '100px' : '32px',
-                                  ? `Generate speech for "${currentStory.name}"...`
+                                  maxHeight: '300px',
-                                  : selectedProfile
+                                }}
-                                    ? `Generate speech using ${selectedProfile.name}...`
+                                disabled={!selectedProfileId}
-                                    : 'Select a voice profile above...'
+                                onClick={() => setIsExpanded(true)}
-                              }
+                                onFocus={() => setIsExpanded(true)}
-                              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',
-                                maxHeight: '300px',
-                              }}
-                              disabled={!selectedProfileId}
-                              onClick={() => setIsExpanded(true)}
-                              onFocus={() => setIsExpanded(true)}
-                            />
                           </motion.div>
                         </FormControl>
                         <FormMessage className="text-xs" />
@@ -274,7 +288,7 @@ 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',
@@ -294,20 +308,36 @@ export function FloatingGenerateBox({
               </motion.div>
 
               <div className="relative shrink-0">
-                <Button
+                <div className="group relative">
-                  type="submit"
+                  <Button
-                  disabled={isPending || !selectedProfileId}
+                    type="submit"
-                  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"
+                    disabled={isPending || !selectedProfileId}
-                  size="icon"
+                    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 ? (
+                    aria-label={
-                    <Loader2 className="h-4 w-4 animate-spin" />
+                      isPending
-                  ) : (
+                        ? 'Generating...'
-                    <Sparkles className="h-4 w-4" />
+                        : !selectedProfileId
-                  )}
+                          ? 'Select a voice profile first'
-                </Button>
+                          : 'Generate speech'
+                    }
+                  >
+                    {isPending ? (
+                      <Loader2 className="h-4 w-4 animate-spin" />
+                    ) : (
+                      <Sparkles 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 && (
+                  {isExpanded && form.watch('engine') === 'qwen' && (
                     <motion.div
                       initial={{ opacity: 0, scale: 0.8 }}
                       animate={{ opacity: 1, scale: 1 }}
@@ -315,20 +345,28 @@ export function FloatingGenerateBox({
                       transition={{ duration: 0.2 }}
                       className="absolute top-0 right-[calc(100%+0.5rem)]"
                     >
-                      <Button
+                      <div className="group relative">
-                        type="button"
+                        <Button
-                        variant="ghost"
+                          type="button"
-                        size="icon"
+                          variant="ghost"
-                        onClick={() => setIsInstructMode(!isInstructMode)}
+                          size="icon"
-                        className={cn(
+                          onClick={() => setIsInstructMode(!isInstructMode)}
-                          'h-10 w-10 rounded-full transition-all duration-200',
+                          className={cn(
-                          isInstructMode
+                            'h-10 w-10 rounded-full transition-all duration-200',
-                            ? 'bg-accent text-accent-foreground border border-accent hover:bg-accent/90'
+                            isInstructMode
-                            : 'bg-card border border-border hover:bg-background/50',
+                              ? '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" />
+                          aria-label={
-                      </Button>
+                            isInstructMode ? 'Fine tune instructions, on' : 'Fine tune instructions'
+                          }
+                        >
+                          <SlidersHorizontal 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>
@@ -367,51 +405,86 @@ export function FloatingGenerateBox({
                   <FormField
                     control={form.control}
                     name="language"
-                    render={({ field }) => (
+                    render={({ field }) => {
-                      <FormItem className="flex-1 space-y-0">
+                      const engineLangs = getLanguageOptionsForEngine(
-                        <Select onValueChange={field.onChange} defaultValue={field.value}>
+                        form.watch('engine') || 'qwen',
-                          <FormControl>
+                      );
-                            <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
+                      return (
-                              <SelectValue />
+                        <FormItem className="flex-1 space-y-0">
-                            </SelectTrigger>
+                          <Select onValueChange={field.onChange} value={field.value}>
-                          </FormControl>
+                            <FormControl>
-                          <SelectContent>
+                              <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
-                            {LANGUAGE_OPTIONS.map((lang) => (
+                                <SelectValue />
-                              <SelectItem key={lang.value} value={lang.value} className="text-xs">
+                              </SelectTrigger>
-                                {lang.label}
+                            </FormControl>
-                              </SelectItem>
+                            <SelectContent>
-                            ))}
+                              {engineLangs.map((lang) => (
-                          </SelectContent>
+                                <SelectItem key={lang.value} value={lang.value} className="text-xs">
-                        </Select>
+                                  {lang.label}
-                        <FormMessage className="text-xs" />
+                                </SelectItem>
-                      </FormItem>
+                              ))}
-                    )}
+                            </SelectContent>
+                          </Select>
+                          <FormMessage className="text-xs" />
+                        </FormItem>
+                      );
+                    }}
                   />
 
-                  <FormField
+                  <FormItem className="flex-1 space-y-0">
-                    control={form.control}
+                    <Select
-                    name="modelSize"
+                      value={
-                    render={({ field }) => (
+                        form.watch('engine') === 'luxtts'
-                      <FormItem className="flex-1 space-y-0">
+                          ? 'luxtts'
-                        <Select onValueChange={field.onChange} defaultValue={field.value}>
+                          : form.watch('engine') === 'chatterbox'
-                          <FormControl>
+                            ? 'chatterbox'
-                            <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
+                            : form.watch('engine') === 'chatterbox_turbo'
-                              <SelectValue />
+                              ? 'chatterbox_turbo'
-                            </SelectTrigger>
+                              : `qwen:${form.watch('modelSize') || '1.7B'}`
-                          </FormControl>
+                      }
-                          <SelectContent>
+                      onValueChange={(value) => {
-                            <SelectItem value="1.7B" className="text-xs text-muted-foreground">
+                        if (value === 'luxtts') {
-                              Qwen3-TTS 1.7B
+                          form.setValue('engine', 'luxtts');
-                            </SelectItem>
+                          form.setValue('language', 'en');
-                            <SelectItem value="0.6B" className="text-xs text-muted-foreground">
+                        } else if (value === 'chatterbox') {
-                              Qwen3-TTS 0.6B
+                          form.setValue('engine', 'chatterbox');
-                            </SelectItem>
+                        } else if (value === 'chatterbox_turbo') {
-                          </SelectContent>
+                          form.setValue('engine', 'chatterbox_turbo');
-                        </Select>
+                          form.setValue('language', 'en');
-                        <FormMessage className="text-xs" />
+                        } else {
-                      </FormItem>
+                          const [, modelSize] = value.split(':');
-                    )}
+                          form.setValue('engine', 'qwen');
-                  />
+                          form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
+                        }
+                      }}
+                    >
+                      <FormControl>
+                        <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
+                          <SelectValue />
+                        </SelectTrigger>
+                      </FormControl>
+                      <SelectContent>
+                        <SelectItem value="qwen:1.7B" className="text-xs text-muted-foreground">
+                          Qwen3-TTS 1.7B
+                        </SelectItem>
+                        <SelectItem value="qwen:0.6B" className="text-xs text-muted-foreground">
+                          Qwen3-TTS 0.6B
+                        </SelectItem>
+                        <SelectItem value="luxtts" className="text-xs text-muted-foreground">
+                          LuxTTS
+                        </SelectItem>
+                        <SelectItem value="chatterbox" className="text-xs text-muted-foreground">
+                          Chatterbox
+                        </SelectItem>
+                        <SelectItem
+                          value="chatterbox_turbo"
+                          className="text-xs text-muted-foreground"
+                        >
+                          Chatterbox Turbo
+                        </SelectItem>
+                      </SelectContent>
+                    </Select>
+                  </FormItem>
                 </div>
               </motion.div>
             </AnimatePresence>

app/src/components/Generation/GenerationForm.tsx

@@ -19,10 +19,11 @@ import {
   SelectValue,
 } from '@/components/ui/select';
 import { Textarea } from '@/components/ui/textarea';
-import { LANGUAGE_OPTIONS } from '@/lib/constants/languages';
+import { getLanguageOptionsForEngine } from '@/lib/constants/languages';
 import { useGenerationForm } from '@/lib/hooks/useGenerationForm';
 import { useProfile } from '@/lib/hooks/useProfiles';
 import { useUIStore } from '@/stores/uiStore';
+import { ParalinguisticInput } from './ParalinguisticInput';
 
 export function GenerationForm() {
   const selectedProfileId = useUIStore((state) => state.selectedProfileId);
@@ -64,87 +65,134 @@ export function GenerationForm() {
                 <FormItem>
                   <FormLabel>Text to Speak</FormLabel>
                   <FormControl>
-                    <Textarea
+                    {form.watch('engine') === 'chatterbox_turbo' ? (
-                      placeholder="Enter the text you want to generate..."
+                      <ParalinguisticInput
-                      className="min-h-[150px]"
+                        value={field.value}
-                      {...field}
+                        onChange={field.onChange}
-                    />
+                        placeholder="Enter text... type / for effects like [laugh], [sigh]"
-                  </FormControl>
+                        className="min-h-[150px] rounded-md border border-input bg-background px-3 py-2"
-                  <FormDescription>Max 5000 characters</FormDescription>
+                      />
-                  <FormMessage />
+                    ) : (
-                </FormItem>
+                      <Textarea
-              )}
+                        placeholder="Enter the text you want to generate..."
-            />
+                        className="min-h-[150px]"
-
+                        {...field}
-            <FormField
+                      />
-              control={form.control}
+                    )}
-              name="instruct"
-              render={({ field }) => (
-                <FormItem>
-                  <FormLabel>Delivery Instructions (optional)</FormLabel>
-                  <FormControl>
-                    <Textarea
-                      placeholder="e.g. Speak slowly with emphasis, Warm and friendly tone, Professional and authoritative..."
-                      className="min-h-[80px]"
-                      {...field}
-                    />
                   </FormControl>
                   <FormDescription>
-                    Natural language instructions to control speech delivery (tone, emotion, pace).
+                    {form.watch('engine') === 'chatterbox_turbo'
-                    Max 500 characters
+                      ? 'Max 5000 characters. Type / to insert sound effects.'
+                      : 'Max 5000 characters'}
                   </FormDescription>
                   <FormMessage />
                 </FormItem>
               )}
             />
 
-            <div className="grid gap-4 md:grid-cols-3">
+            {form.watch('engine') === 'qwen' && (
               <FormField
                 control={form.control}
-                name="language"
+                name="instruct"
                 render={({ field }) => (
                   <FormItem>
-                    <FormLabel>Language</FormLabel>
+                    <FormLabel>Delivery Instructions (optional)</FormLabel>
-                    <Select onValueChange={field.onChange} defaultValue={field.value}>
+                    <FormControl>
-                      <FormControl>
+                      <Textarea
-                        <SelectTrigger>
+                        placeholder="e.g. Speak slowly with emphasis, Warm and friendly tone, Professional and authoritative..."
-                          <SelectValue />
+                        className="min-h-[80px]"
-                        </SelectTrigger>
+                        {...field}
-                      </FormControl>
+                      />
-                      <SelectContent>
+                    </FormControl>
-                        {LANGUAGE_OPTIONS.map((lang) => (
+                    <FormDescription>
-                          <SelectItem key={lang.value} value={lang.value}>
+                      Natural language instructions to control speech delivery (tone, emotion,
-                            {lang.label}
+                      pace). Max 500 characters
-                          </SelectItem>
+                    </FormDescription>
-                        ))}
-                      </SelectContent>
-                    </Select>
                     <FormMessage />
                   </FormItem>
                 )}
               />
+            )}
+
+            <div className="grid gap-4 md:grid-cols-3">
+              <FormItem>
+                <FormLabel>Model</FormLabel>
+                <Select
+                  value={
+                    form.watch('engine') === 'luxtts'
+                      ? 'luxtts'
+                      : form.watch('engine') === 'chatterbox'
+                        ? 'chatterbox'
+                        : form.watch('engine') === 'chatterbox_turbo'
+                          ? 'chatterbox_turbo'
+                          : `qwen:${form.watch('modelSize') || '1.7B'}`
+                  }
+                  onValueChange={(value) => {
+                    if (value === 'luxtts') {
+                      form.setValue('engine', 'luxtts');
+                      form.setValue('language', 'en');
+                    } else if (value === 'chatterbox') {
+                      form.setValue('engine', 'chatterbox');
+                    } else if (value === 'chatterbox_turbo') {
+                      form.setValue('engine', 'chatterbox_turbo');
+                      form.setValue('language', 'en');
+                    } else {
+                      const [, modelSize] = value.split(':');
+                      form.setValue('engine', 'qwen');
+                      form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
+                    }
+                  }}
+                >
+                  <FormControl>
+                    <SelectTrigger>
+                      <SelectValue />
+                    </SelectTrigger>
+                  </FormControl>
+                  <SelectContent>
+                    <SelectItem value="qwen:1.7B">Qwen3-TTS 1.7B</SelectItem>
+                    <SelectItem value="qwen:0.6B">Qwen3-TTS 0.6B</SelectItem>
+                    <SelectItem value="luxtts">LuxTTS</SelectItem>
+                    <SelectItem value="chatterbox">Chatterbox</SelectItem>
+                    <SelectItem value="chatterbox_turbo">Chatterbox Turbo</SelectItem>
+                  </SelectContent>
+                </Select>
+                <FormDescription>
+                  {form.watch('engine') === 'luxtts'
+                    ? 'Fast, English-focused'
+                    : form.watch('engine') === 'chatterbox'
+                      ? '23 languages, incl. Hebrew'
+                      : form.watch('engine') === 'chatterbox_turbo'
+                        ? 'English, [laugh] [cough] tags'
+                        : 'Multi-language, two sizes'}
+                </FormDescription>
+              </FormItem>
 
               <FormField
                 control={form.control}
-                name="modelSize"
+                name="language"
-                render={({ field }) => (
+                render={({ field }) => {
-                  <FormItem>
+                  const engineLangs = getLanguageOptionsForEngine(form.watch('engine') || 'qwen');
-                    <FormLabel>Model Size</FormLabel>
+                  return (
-                    <Select onValueChange={field.onChange} defaultValue={field.value}>
+                    <FormItem>
-                      <FormControl>
+                      <FormLabel>Language</FormLabel>
-                        <SelectTrigger>
+                      <Select onValueChange={field.onChange} value={field.value}>
-                          <SelectValue />
+                        <FormControl>
-                        </SelectTrigger>
+                          <SelectTrigger>
-                      </FormControl>
+                            <SelectValue />
-                      <SelectContent>
+                          </SelectTrigger>
-                        <SelectItem value="1.7B">Qwen TTS 1.7B (Higher Quality)</SelectItem>
+                        </FormControl>
-                        <SelectItem value="0.6B">Qwen TTS 0.6B (Faster)</SelectItem>
+                        <SelectContent>
-                      </SelectContent>
+                          {engineLangs.map((lang) => (
-                    </Select>
+                            <SelectItem key={lang.value} value={lang.value}>
-                    <FormDescription>Larger models produce better quality</FormDescription>
+                              {lang.label}
-                    <FormMessage />
+                            </SelectItem>
-                  </FormItem>
+                          ))}
-                )}
+                        </SelectContent>
+                      </Select>
+                      <FormMessage />
+                    </FormItem>
+                  );
+                }}
               />
 
               <FormField
@@ -170,11 +218,7 @@ export function GenerationForm() {
               />
             </div>
 
-            <Button
+            <Button type="submit" className="w-full" disabled={isPending || !selectedProfileId}>
-              type="submit"
-              className="w-full"
-              disabled={isPending || !selectedProfileId}
-            >
               {isPending ? (
                 <>
                   <Loader2 className="mr-2 h-4 w-4 animate-spin" />

app/src/components/Generation/ParalinguisticInput.tsx

@@ -0,0 +1,422 @@
+/**
+ * ParalinguisticInput — a contentEditable rich text input that renders
+ * Chatterbox Turbo paralinguistic tags (e.g. [laugh]) as inline badges.
+ *
+ * Trigger: typing "/" opens an autocomplete dropdown.
+ * Paste:   pasting text with [tag] patterns auto-converts to badges.
+ * Output:  serializes badges back to plain [tag] text for the API.
+ */
+
+import { AnimatePresence, motion } from 'framer-motion';
+import { forwardRef, useCallback, useEffect, useImperativeHandle, useRef, useState } from 'react';
+import { createPortal } from 'react-dom';
+import { cn } from '@/lib/utils/cn';
+
+// ── Tag definitions ─────────────────────────────────────────────────
+const PARALINGUISTIC_TAGS = [
+  { tag: '[laugh]', label: 'laugh', emoji: '\u{1F602}' },
+  { tag: '[chuckle]', label: 'chuckle', emoji: '\u{1F60F}' },
+  { tag: '[gasp]', label: 'gasp', emoji: '\u{1F62E}' },
+  { tag: '[cough]', label: 'cough', emoji: '\u{1F637}' },
+  { tag: '[sigh]', label: 'sigh', emoji: '\u{1F614}' },
+  { tag: '[groan]', label: 'groan', emoji: '\u{1F629}' },
+  { tag: '[sniff]', label: 'sniff', emoji: '\u{1F443}' },
+  { tag: '[shush]', label: 'shush', emoji: '\u{1F92B}' },
+  { tag: '[clear throat]', label: 'clear throat', emoji: '\u{1F64A}' },
+] as const;
+
+const TAG_REGEX = /\[(laugh|chuckle|gasp|cough|sigh|groan|sniff|shush|clear throat)\]/gi;
+
+// Data attribute used to identify badge spans in the DOM
+const BADGE_ATTR = 'data-ptag';
+
+// ── Helpers ─────────────────────────────────────────────────────────
+
+/** Build an inline badge <span> for a tag. */
+function makeBadgeHTML(tag: string): string {
+  const entry = PARALINGUISTIC_TAGS.find((t) => t.tag.toLowerCase() === tag.toLowerCase());
+  const label = entry?.label ?? tag.replace(/[[\]]/g, '');
+  const emoji = entry?.emoji ?? '';
+  // Non-editable inline badge. Zero-width spaces around it let the
+  // caret sit on either side so the user can type before/after.
+  return `\u200B<span ${BADGE_ATTR}="${tag}" contenteditable="false" class="ptag-badge">${emoji ? `${emoji}\u00A0` : ''}${label}</span>\u200B`;
+}
+
+/** Convert plain text with [tag] patterns into HTML with badge spans. */
+function textToHTML(text: string): string {
+  // Escape HTML entities first
+  const escaped = text.replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;');
+  // Replace tag patterns with badge HTML
+  return escaped.replace(TAG_REGEX, (match) => makeBadgeHTML(match));
+}
+
+/** Serialize the contentEditable innerHTML back to plain text with [tag] syntax. */
+function htmlToText(container: HTMLElement): string {
+  let result = '';
+  for (const node of container.childNodes) {
+    if (node.nodeType === Node.TEXT_NODE) {
+      // Strip zero-width spaces we added around badges
+      result += (node.textContent ?? '').replace(/\u200B/g, '');
+    } else if (node.nodeType === Node.ELEMENT_NODE) {
+      const el = node as HTMLElement;
+      if (el.hasAttribute(BADGE_ATTR)) {
+        result += el.getAttribute(BADGE_ATTR) ?? '';
+      } else if (el.tagName === 'BR') {
+        result += '\n';
+      } else {
+        // Recurse for nested elements (e.g. spans from paste)
+        result += htmlToText(el);
+      }
+    }
+  }
+  return result;
+}
+
+/** Get the text content from the current caret position back to the last
+ *  whitespace or start of container, to detect the "/" trigger. */
+function getWordBeforeCaret(_container: HTMLElement): { word: string; range: Range | null } {
+  const sel = window.getSelection();
+  if (!sel || sel.rangeCount === 0) return { word: '', range: null };
+  const range = sel.getRangeAt(0).cloneRange();
+  range.collapse(true);
+
+  // Walk backwards from caret through the text node
+  const textNode = range.startContainer;
+  if (textNode.nodeType !== Node.TEXT_NODE) return { word: '', range: null };
+  const text = textNode.textContent ?? '';
+  const offset = range.startOffset;
+
+  let start = offset;
+  while (
+    start > 0 &&
+    text[start - 1] !== ' ' &&
+    text[start - 1] !== '\n' &&
+    text[start - 1] !== '\u00A0'
+  ) {
+    start--;
+  }
+
+  const word = text.slice(start, offset);
+  const wordRange = document.createRange();
+  wordRange.setStart(textNode, start);
+  wordRange.setEnd(textNode, offset);
+
+  return { word, range: wordRange };
+}
+
+// ── Component ───────────────────────────────────────────────────────
+
+export interface ParalinguisticInputProps {
+  value?: string;
+  onChange?: (value: string) => void;
+  placeholder?: string;
+  disabled?: boolean;
+  className?: string;
+  style?: React.CSSProperties;
+  onClick?: () => void;
+  onFocus?: () => void;
+}
+
+export interface ParalinguisticInputRef {
+  focus: () => void;
+  element: HTMLDivElement | null;
+}
+
+export const ParalinguisticInput = forwardRef<ParalinguisticInputRef, ParalinguisticInputProps>(
+  function ParalinguisticInput(
+    { value, onChange, placeholder, disabled, className, style, onClick, onFocus },
+    ref,
+  ) {
+    const editorRef = useRef<HTMLDivElement>(null);
+    const [showMenu, setShowMenu] = useState(false);
+    const [menuFilter, setMenuFilter] = useState('');
+    const [menuIndex, setMenuIndex] = useState(0);
+    const [menuPosition, setMenuPosition] = useState<{ bottom: number; left: number }>({
+      bottom: 0,
+      left: 0,
+    });
+    const triggerRangeRef = useRef<Range | null>(null);
+    const lastSerializedRef = useRef<string>('');
+    const isComposingRef = useRef(false);
+
+    useImperativeHandle(ref, () => ({
+      focus: () => editorRef.current?.focus(),
+      element: editorRef.current,
+    }));
+
+    // Filtered tag list for the autocomplete menu
+    const filteredTags = PARALINGUISTIC_TAGS.filter((t) =>
+      t.label.toLowerCase().includes(menuFilter.toLowerCase()),
+    );
+
+    // ── Sync external value → editor ──────────────────────────────
+    useEffect(() => {
+      const el = editorRef.current;
+      if (!el) return;
+      // Only update DOM if the external value differs from what we last emitted
+      if (value !== undefined && value !== lastSerializedRef.current) {
+        lastSerializedRef.current = value;
+        el.innerHTML = value ? textToHTML(value) : '';
+      }
+    }, [value]);
+
+    // ── Emit plain-text value on input ────────────────────────────
+    const emitChange = useCallback(() => {
+      const el = editorRef.current;
+      if (!el || !onChange) return;
+      const text = htmlToText(el);
+      lastSerializedRef.current = text;
+      onChange(text);
+    }, [onChange]);
+
+    // ── Insert a tag badge at the caret ───────────────────────────
+    const insertTag = useCallback(
+      (tag: string) => {
+        const el = editorRef.current;
+        if (!el) return;
+
+        // Delete the /filter text
+        const wordRange = triggerRangeRef.current;
+        if (wordRange) {
+          wordRange.deleteContents();
+        }
+
+        // Insert badge HTML
+        const temp = document.createElement('span');
+        temp.innerHTML = makeBadgeHTML(tag);
+        const frag = document.createDocumentFragment();
+        let lastNode: Node | null = null;
+        while (temp.firstChild) {
+          lastNode = frag.appendChild(temp.firstChild);
+        }
+
+        const sel = window.getSelection();
+        if (sel && sel.rangeCount > 0) {
+          const range = sel.getRangeAt(0);
+          range.deleteContents();
+          range.insertNode(frag);
+
+          // Move caret after the badge
+          if (lastNode) {
+            const newRange = document.createRange();
+            newRange.setStartAfter(lastNode);
+            newRange.collapse(true);
+            sel.removeAllRanges();
+            sel.addRange(newRange);
+          }
+        }
+
+        setShowMenu(false);
+        setMenuFilter('');
+        emitChange();
+        el.focus();
+      },
+      [emitChange],
+    );
+
+    // ── Handle keydown for autocomplete navigation ────────────────
+    const handleKeyDown = useCallback(
+      (e: React.KeyboardEvent) => {
+        if (showMenu) {
+          if (filteredTags.length === 0) {
+            if (e.key === 'Escape') {
+              e.preventDefault();
+              setShowMenu(false);
+            }
+            return;
+          }
+          if (e.key === 'ArrowDown') {
+            e.preventDefault();
+            setMenuIndex((i) => (i + 1) % filteredTags.length);
+          } else if (e.key === 'ArrowUp') {
+            e.preventDefault();
+            setMenuIndex((i) => (i - 1 + filteredTags.length) % filteredTags.length);
+          } else if (e.key === 'Enter' || e.key === 'Tab') {
+            e.preventDefault();
+            if (filteredTags[menuIndex]) {
+              insertTag(filteredTags[menuIndex].tag);
+            }
+          } else if (e.key === 'Escape') {
+            e.preventDefault();
+            setShowMenu(false);
+          }
+        } else {
+          // Prevent Enter from creating <div> blocks in contentEditable
+          if (e.key === 'Enter' && !e.shiftKey) {
+            // Let the form handle submit
+          }
+        }
+      },
+      [showMenu, filteredTags, menuIndex, insertTag],
+    );
+
+    // ── Handle input (check for / trigger) ────────────────────────
+    const handleInput = useCallback(() => {
+      if (isComposingRef.current) return;
+      const el = editorRef.current;
+      if (!el) return;
+
+      const { word, range } = getWordBeforeCaret(el);
+
+      if (word.startsWith('/')) {
+        const filter = word.slice(1); // strip the /
+        setMenuFilter(filter);
+        setMenuIndex(0);
+        triggerRangeRef.current = range;
+
+        // Position the menu above the caret using viewport coords (portalled)
+        const sel = window.getSelection();
+        if (sel && sel.rangeCount > 0) {
+          const rect = sel.getRangeAt(0).getBoundingClientRect();
+          setMenuPosition({
+            bottom: window.innerHeight - rect.top + 4,
+            left: rect.left,
+          });
+        }
+
+        setShowMenu(true);
+      } else {
+        setShowMenu(false);
+      }
+
+      emitChange();
+    }, [emitChange]);
+
+    // ── Handle paste — convert [tag] patterns to badges ───────────
+    const handlePaste = useCallback(
+      (e: React.ClipboardEvent) => {
+        e.preventDefault();
+        const text = e.clipboardData.getData('text/plain');
+        if (!text) return;
+
+        const el = editorRef.current;
+        if (!el) return;
+
+        const html = textToHTML(text);
+
+        // Insert at caret
+        const sel = window.getSelection();
+        if (sel && sel.rangeCount > 0) {
+          const range = sel.getRangeAt(0);
+          range.deleteContents();
+          const temp = document.createElement('div');
+          temp.innerHTML = html;
+          const frag = document.createDocumentFragment();
+          let lastNode: Node | null = null;
+          while (temp.firstChild) {
+            lastNode = frag.appendChild(temp.firstChild);
+          }
+          range.insertNode(frag);
+          if (lastNode) {
+            const newRange = document.createRange();
+            newRange.setStartAfter(lastNode);
+            newRange.collapse(true);
+            sel.removeAllRanges();
+            sel.addRange(newRange);
+          }
+        }
+
+        emitChange();
+      },
+      [emitChange],
+    );
+
+    // ── Show placeholder ──────────────────────────────────────────
+    const isEmpty = !value || value.trim() === '';
+
+    return (
+      <div className="relative">
+        {/* Placeholder */}
+        {isEmpty && placeholder && (
+          <div
+            className="pointer-events-none absolute inset-0 text-sm text-muted-foreground/60 px-3 py-2 select-none"
+            aria-hidden
+          >
+            {placeholder}
+          </div>
+        )}
+
+        {/* Editable area */}
+        <div
+          ref={editorRef}
+          contentEditable={!disabled}
+          suppressContentEditableWarning
+          role={disabled ? undefined : 'textbox'}
+          aria-multiline={disabled ? undefined : true}
+          aria-placeholder={placeholder}
+          aria-disabled={disabled}
+          tabIndex={disabled ? -1 : 0}
+          className={cn(
+            'min-h-[32px] text-sm whitespace-pre-wrap break-words outline-none',
+            '[&_.ptag-badge]:inline-flex [&_.ptag-badge]:items-center [&_.ptag-badge]:rounded-full',
+            '[&_.ptag-badge]:bg-accent/20 [&_.ptag-badge]:text-accent [&_.ptag-badge]:border [&_.ptag-badge]:border-accent/30',
+            '[&_.ptag-badge]:px-2 [&_.ptag-badge]:py-0 [&_.ptag-badge]:text-xs [&_.ptag-badge]:font-medium',
+            '[&_.ptag-badge]:mx-0.5 [&_.ptag-badge]:select-none [&_.ptag-badge]:cursor-default',
+            '[&_.ptag-badge]:align-baseline',
+            disabled && 'opacity-50 cursor-not-allowed',
+            className,
+          )}
+          style={style}
+          onInput={!disabled ? handleInput : undefined}
+          onKeyDown={!disabled ? handleKeyDown : undefined}
+          onPaste={!disabled ? handlePaste : undefined}
+          onClick={!disabled ? onClick : undefined}
+          onFocus={!disabled ? onFocus : undefined}
+          onBlur={() => {
+            setShowMenu(false);
+            triggerRangeRef.current = null;
+          }}
+          onCompositionStart={() => {
+            isComposingRef.current = true;
+          }}
+          onCompositionEnd={() => {
+            isComposingRef.current = false;
+            handleInput();
+          }}
+        />
+
+        {/* Autocomplete dropdown — portalled to body, positioned above the caret */}
+        {showMenu &&
+          filteredTags.length > 0 &&
+          createPortal(
+            <AnimatePresence>
+              <motion.div
+                initial={{ opacity: 0, y: 4 }}
+                animate={{ opacity: 1, y: 0 }}
+                exit={{ opacity: 0, y: 4 }}
+                transition={{ duration: 0.12 }}
+                className="fixed z-[9999] min-w-[200px] max-h-[280px] overflow-y-auto rounded-lg border border-border bg-popover shadow-lg"
+                style={{
+                  bottom: menuPosition.bottom,
+                  left: menuPosition.left,
+                }}
+              >
+                {filteredTags.map((t, i) => (
+                  <button
+                    key={t.tag}
+                    type="button"
+                    className={cn(
+                      'flex items-center gap-2 w-full px-3 py-1.5 text-sm text-left transition-colors',
+                      i === menuIndex
+                        ? 'bg-accent/20 text-accent-foreground'
+                        : 'text-popover-foreground hover:bg-muted/50',
+                    )}
+                    onMouseDown={(e) => {
+                      e.preventDefault(); // Keep focus in editor
+                      insertTag(t.tag);
+                    }}
+                    onMouseEnter={() => setMenuIndex(i)}
+                  >
+                    <span className="text-base leading-none">{t.emoji}</span>
+                    <span>{t.label}</span>
+                    <span className="ml-auto text-xs text-muted-foreground font-mono">{t.tag}</span>
+                  </button>
+                ))}
+              </motion.div>
+            </AnimatePresence>,
+            document.body,
+          )}
+      </div>
+    );
+  },
+);

app/src/components/History/HistoryTable.tsx

@@ -1,6 +1,15 @@
-import { AudioWaveform, Download, FileArchive, Loader2, MoreHorizontal, Play, Trash2 } from 'lucide-react';
+import { useQueryClient } from '@tanstack/react-query';
+import {
+  Download,
+  FileArchive,
+  Loader2,
+  MoreHorizontal,
+  Play,
+  RotateCcw,
+  Trash2,
+} from 'lucide-react';
 import { useEffect, useRef, useState } from 'react';
-import type { HistoryResponse } from '@/lib/api/types';
+import Loader from 'react-loaders';
 import { Button } from '@/components/ui/button';
 import {
   Dialog,
@@ -19,6 +28,7 @@ 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,
@@ -28,7 +38,8 @@ import {
   useImportGeneration,
 } from '@/lib/hooks/useHistory';
 import { cn } from '@/lib/utils/cn';
-import { formatDate, formatDuration } from '@/lib/utils/format';
+import { formatDate, formatDuration, formatEngineName } from '@/lib/utils/format';
+import { useGenerationStore } from '@/stores/generationStore';
 import { usePlayerStore } from '@/stores/playerStore';
 
 // OLD TABLE-BASED COMPONENT - REMOVED (can be found in git history)
@@ -46,11 +57,18 @@ export function HistoryTable() {
   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 [generationToDelete, setGenerationToDelete] = useState<{ id: string; name: string } | null>(
+    null,
+  );
   const limit = 20;
   const { toast } = useToast();
+  const queryClient = useQueryClient();
 
-  const { data: historyData, isLoading, isFetching } = useHistory({
+  const {
+    data: historyData,
+    isLoading,
+    isFetching,
+  } = useHistory({
     limit,
     offset: page * limit,
   });
@@ -59,6 +77,7 @@ export function HistoryTable() {
   const exportGeneration = useExportGeneration();
   const exportGenerationAudio = useExportGenerationAudio();
   const importGeneration = useImportGeneration();
+  const addPendingGeneration = useGenerationStore((state) => state.addPendingGeneration);
   const setAudioWithAutoPlay = usePlayerStore((state) => state.setAudioWithAutoPlay);
   const restartCurrentAudio = usePlayerStore((state) => state.restartCurrentAudio);
   const currentAudioId = usePlayerStore((state) => state.audioId);
@@ -182,6 +201,20 @@ export function HistoryTable() {
     }
   };
 
+  const handleRetry = async (generationId: string) => {
+    try {
+      const result = await apiClient.retryGeneration(generationId);
+      addPendingGeneration(result.id);
+      queryClient.invalidateQueries({ queryKey: ['history'] });
+    } catch (error) {
+      toast({
+        title: 'Retry failed',
+        description: error instanceof Error ? error.message : 'Could not retry generation',
+        variant: 'destructive',
+      });
+    }
+  };
+
   const handleImportConfirm = () => {
     if (selectedFile) {
       importGeneration.mutate(selectedFile, {
@@ -238,25 +271,54 @@ export function HistoryTable() {
           >
             {history.map((gen) => {
               const isCurrentlyPlaying = currentAudioId === gen.id && isPlaying;
+              const isGenerating = gen.status === 'generating';
+              const isFailed = gen.status === 'failed';
+              const isPlayable = !isGenerating && !isFailed;
               return (
                 <div
                   key={gen.id}
+                  role={isPlayable ? 'button' : undefined}
+                  tabIndex={isPlayable ? 0 : undefined}
                   className={cn(
-                    'flex items-stretch gap-4 h-26 border rounded-md p-3 bg-card hover:bg-muted/70 transition-colors text-left w-full',
+                    'flex items-stretch gap-4 h-26 border rounded-md p-3 bg-card transition-colors text-left w-full',
+                    isPlayable && 'hover:bg-muted/70 cursor-pointer',
                     isCurrentlyPlaying && 'bg-muted/70',
                   )}
+                  aria-label={
+                    isGenerating
+                      ? `Generating speech for ${gen.profile_name}...`
+                      : isFailed
+                        ? `Generation failed for ${gen.profile_name}`
+                        : isCurrentlyPlaying
+                          ? `Sample from ${gen.profile_name}, ${formatDuration(gen.duration ?? 0)}, ${formatDate(gen.created_at)}. Playing. Press Enter to restart.`
+                          : `Sample from ${gen.profile_name}, ${formatDuration(gen.duration ?? 0)}, ${formatDate(gen.created_at)}. Press Enter to play.`
+                  }
                   onMouseDown={(e) => {
-                    // Don't trigger play if clicking on textarea or if text is selected
+                    if (!isPlayable) return;
                     const target = e.target as HTMLElement;
                     if (target.closest('textarea') || window.getSelection()?.toString()) {
                       return;
                     }
                     handlePlay(gen.id, gen.text, gen.profile_id);
                   }}
+                  onKeyDown={(e) => {
+                    if (!isPlayable) return;
+                    const target = e.target as HTMLElement;
+                    if (target.closest('textarea') || target.closest('button')) return;
+                    if (e.key === 'Enter' || e.key === ' ') {
+                      e.preventDefault();
+                      handlePlay(gen.id, gen.text, gen.profile_id);
+                    }
+                  }}
                 >
-                  {/* Waveform icon */}
+                  {/* Status icon */}
-                  <div className="flex items-center shrink-0">
+                  <div className="flex items-center shrink-0 w-10 justify-center overflow-hidden">
-                    <AudioWaveform className="h-5 w-5 text-muted-foreground" />
+                    <div className="scale-50">
+                      <Loader
+                        type={isGenerating ? 'line-scale' : 'line-scale-pulse-out-rapid'}
+                        active={isGenerating || isCurrentlyPlaying}
+                      />
+                    </div>
                   </div>
 
                   {/* Left side - Meta information */}
@@ -267,11 +329,22 @@ export function HistoryTable() {
                     <div className="flex items-center gap-2">
                       <span className="text-xs text-muted-foreground">{gen.language}</span>
                       <span className="text-xs text-muted-foreground">
-                        {formatDuration(gen.duration)}
+                        {formatEngineName(gen.engine, gen.model_size)}
                       </span>
+                      {isFailed ? (
+                        <span className="text-xs text-destructive">Failed</span>
+                      ) : !isGenerating ? (
+                        <span className="text-xs text-muted-foreground">
+                          {formatDuration(gen.duration ?? 0)}
+                        </span>
+                      ) : null}
                     </div>
                     <div className="text-xs text-muted-foreground">
-                      {formatDate(gen.created_at)}
+                      {isGenerating ? (
+                        <span className="text-accent">Generating...</span>
+                      ) : (
+                        formatDate(gen.created_at)
+                      )}
                     </div>
                   </div>
 
@@ -280,57 +353,71 @@ export function HistoryTable() {
                     <Textarea
                       value={gen.text}
                       className="flex-1 resize-none text-sm text-muted-foreground select-text"
+                      readOnly
+                      aria-label={`Transcript for sample from ${gen.profile_name}, ${formatDuration(gen.duration ?? 0)}`}
                     />
                   </div>
 
-                  {/* Far right - Ellipsis actions */}
+                  {/* Far right - Actions */}
                   <div
-                    className="w-10 shrink-0 flex justify-end"
+                    className="w-10 shrink-0 flex justify-end items-center"
                     onMouseDown={(e) => e.stopPropagation()}
                     onClick={(e) => e.stopPropagation()}
                   >
-                    <DropdownMenu>
+                    {isFailed ? (
-                      <DropdownMenuTrigger asChild>
+                      <Button
-                        <Button
+                        variant="ghost"
-                          variant="ghost"
+                        size="icon"
-                          size="icon"
+                        className="h-8 w-8"
-                          className="h-8 w-8"
+                        aria-label="Retry generation"
-                          aria-label="Actions"
+                        onClick={() => handleRetry(gen.id)}
-                        >
+                      >
-                          <MoreHorizontal className="h-4 w-4" />
+                        <RotateCcw className="h-4 w-4" />
-                        </Button>
+                      </Button>
-                      </DropdownMenuTrigger>
+                    ) : isPlayable ? (
-                      <DropdownMenuContent align="end">
+                      <DropdownMenu>
-                        <DropdownMenuItem
+                        <DropdownMenuTrigger asChild>
-                          onClick={() => handlePlay(gen.id, gen.text, gen.profile_id)}
+                          <Button
-                        >
+                            variant="ghost"
-                          <Play className="mr-2 h-4 w-4" />
+                            size="icon"
-                          Play
+                            className="h-8 w-8"
-                        </DropdownMenuItem>
+                            aria-label="Actions"
-                        <DropdownMenuItem
+                          >
-                          onClick={() => handleDownloadAudio(gen.id, gen.text)}
+                            <MoreHorizontal className="h-4 w-4" />
-                          disabled={exportGenerationAudio.isPending}
+                          </Button>
-                        >
+                        </DropdownMenuTrigger>
-                          <Download className="mr-2 h-4 w-4" />
+                        <DropdownMenuContent align="end">
-                          Export Audio
+                          <DropdownMenuItem
-                        </DropdownMenuItem>
+                            onClick={() => handlePlay(gen.id, gen.text, gen.profile_id)}
-                        <DropdownMenuItem
+                          >
-                          onClick={() => handleExportPackage(gen.id, gen.text)}
+                            <Play className="mr-2 h-4 w-4" />
-                          disabled={exportGeneration.isPending}
+                            Play
-                        >
+                          </DropdownMenuItem>
-                          <FileArchive className="mr-2 h-4 w-4" />
+                          <DropdownMenuItem
-                          Export Package
+                            onClick={() => handleDownloadAudio(gen.id, gen.text)}
-                        </DropdownMenuItem>
+                            disabled={exportGenerationAudio.isPending}
-                        <DropdownMenuItem
+                          >
-                          onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
+                            <Download className="mr-2 h-4 w-4" />
-                          disabled={deleteGeneration.isPending}
+                            Export Audio
-                          className="text-destructive focus:text-destructive"
+                          </DropdownMenuItem>
-                        >
+                          <DropdownMenuItem
-                          <Trash2 className="mr-2 h-4 w-4" />
+                            onClick={() => handleExportPackage(gen.id, gen.text)}
-                          Delete
+                            disabled={exportGeneration.isPending}
-                        </DropdownMenuItem>
+                          >
-                      </DropdownMenuContent>
+                            <FileArchive className="mr-2 h-4 w-4" />
-                    </DropdownMenu>
+                            Export Package
+                          </DropdownMenuItem>
+                          <DropdownMenuItem
+                            onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
+                            disabled={deleteGeneration.isPending}
+                            className="text-destructive focus:text-destructive"
+                          >
+                            <Trash2 className="mr-2 h-4 w-4" />
+                            Delete
+                          </DropdownMenuItem>
+                        </DropdownMenuContent>
+                      </DropdownMenu>
+                    ) : null}
                   </div>
                 </div>
               );
@@ -358,7 +445,8 @@ export function HistoryTable() {
           <DialogHeader>
             <DialogTitle>Delete Generation</DialogTitle>
             <DialogDescription>
-              Are you sure you want to delete this generation from "{generationToDelete?.name}"? This action cannot be undone.
+              Are you sure you want to delete this generation from "{generationToDelete?.name}"?
+              This action cannot be undone.
             </DialogDescription>
           </DialogHeader>
           <DialogFooter>

app/src/components/MainEditor/MainEditor.tsx

@@ -13,7 +13,7 @@ import {
 } from '@/components/ui/dialog';
 import { useToast } from '@/components/ui/use-toast';
 import { ProfileList } from '@/components/VoiceProfiles/ProfileList';
-import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
+
 import { useImportProfile } from '@/lib/hooks/useProfiles';
 import { cn } from '@/lib/utils/cn';
 import { usePlayerStore } from '@/stores/playerStore';
@@ -77,9 +77,9 @@ export function MainEditor() {
 
   return (
     // Main view: Profiles top left, Generator bottom left, History right
-    <div className="grid grid-cols-1 lg:grid-cols-2 gap-6 h-full min-h-0 overflow-hidden relative">
+    <div className="grid grid-cols-1 lg:grid-cols-2 lg:gap-6 h-full min-h-0 overflow-hidden relative">
       {/* Left Column */}
-      <div className="flex flex-col min-h-0 overflow-hidden relative">
+      <div className="flex flex-col min-h-0 overflow-hidden relative lg:overflow-hidden">
         {/* Scroll Mask - Always visible, behind content */}
         <div className="absolute top-0 left-0 right-0 h-16 bg-gradient-to-b from-background to-transparent z-0 pointer-events-none" />
 
@@ -110,10 +110,7 @@ export function MainEditor() {
         {/* Scrollable Content */}
         <div
           ref={scrollRef}
-          className={cn(
+          className={cn('flex-1 min-h-0 overflow-y-auto pt-14 pb-4', isPlayerVisible && 'lg:pb-32')}
-            'flex-1 min-h-0 overflow-y-auto pt-14',
-            isPlayerVisible ? BOTTOM_SAFE_AREA_PADDING : 'pb-4',
-          )}
         >
           <div className="flex flex-col gap-6">
             <div className="shrink-0 flex flex-col">
@@ -123,6 +120,9 @@ export function MainEditor() {
         </div>
       </div>
 
+      {/* Divider - single column only */}
+      {/* <div className="border-t border-border -my-3 lg:hidden" /> */}
+
       {/* Right Column - History */}
       <div className="flex flex-col min-h-0 overflow-hidden">
         <HistoryTable />

app/src/components/ModelsTab/ModelsTab.tsx

@@ -2,7 +2,7 @@ import { ModelManagement } from '@/components/ServerSettings/ModelManagement';
 
 export function ModelsTab() {
   return (
-    <div className="space-y-4 overflow-y-auto flex flex-col">
+    <div className="h-full flex flex-col">
       <ModelManagement />
     </div>
   );

app/src/components/ServerSettings/ConnectionForm.tsx

@@ -1,9 +1,12 @@
 import { zodResolver } from '@hookform/resolvers/zod';
+import { Loader2, XCircle } from 'lucide-react';
 import { useEffect } from 'react';
 import { useForm } from 'react-hook-form';
 import * as z from 'zod';
+import { Badge } from '@/components/ui/badge';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
+import { Checkbox } from '@/components/ui/checkbox';
 import {
   Form,
   FormControl,
@@ -14,10 +17,10 @@ import {
   FormMessage,
 } from '@/components/ui/form';
 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 { useServerHealth } from '@/lib/hooks/useServer';
 import { usePlatform } from '@/platform/PlatformContext';
+import { useServerStore } from '@/stores/serverStore';
 
 const connectionSchema = z.object({
   serverUrl: z.string().url('Please enter a valid URL'),
@@ -31,7 +34,10 @@ export function ConnectionForm() {
   const setServerUrl = useServerStore((state) => state.setServerUrl);
   const keepServerRunningOnClose = useServerStore((state) => state.keepServerRunningOnClose);
   const setKeepServerRunningOnClose = useServerStore((state) => state.setKeepServerRunningOnClose);
+  const mode = useServerStore((state) => state.mode);
+  const setMode = useServerStore((state) => state.setMode);
   const { toast } = useToast();
+  const { data: health, isLoading, error: healthError } = useServerHealth();
 
   const form = useForm<ConnectionFormValues>({
     resolver: zodResolver(connectionSchema),
@@ -49,7 +55,7 @@ export function ConnectionForm() {
 
   function onSubmit(data: ConnectionFormValues) {
     setServerUrl(data.serverUrl);
-    form.reset(data); // Reset form state after successful submission
+    form.reset(data);
     toast({
       title: 'Server URL updated',
       description: `Connected to ${data.serverUrl}`,
@@ -57,7 +63,7 @@ export function ConnectionForm() {
   }
 
   return (
-    <Card>
+    <Card role="region" aria-label="Server Connection" tabIndex={0}>
       <CardHeader>
         <CardTitle>Server Connection</CardTitle>
       </CardHeader>
@@ -83,10 +89,42 @@ export function ConnectionForm() {
           </form>
         </Form>
 
+        {/* Connection status */}
+        <div className="mt-4">
+          {isLoading ? (
+            <div className="flex items-center gap-2">
+              <Loader2 className="h-4 w-4 animate-spin" />
+              <span className="text-sm text-muted-foreground">Checking connection...</span>
+            </div>
+          ) : healthError ? (
+            <div className="flex items-center gap-2">
+              <XCircle className="h-4 w-4 text-destructive" />
+              <span className="text-sm text-destructive">
+                Connection failed: {healthError.message}
+              </span>
+            </div>
+          ) : health ? (
+            <div className="flex flex-wrap gap-2">
+              <Badge
+                variant={health.model_loaded || health.model_downloaded ? 'default' : 'secondary'}
+              >
+                {health.model_loaded || health.model_downloaded ? 'Model Ready' : 'No Model'}
+              </Badge>
+              <Badge variant={health.gpu_available ? 'default' : 'secondary'}>
+                GPU: {health.gpu_available ? 'Available' : 'Not Available'}
+              </Badge>
+              {health.vram_used_mb && (
+                <Badge variant="outline">VRAM: {health.vram_used_mb.toFixed(0)} MB</Badge>
+              )}
+            </div>
+          ) : null}
+        </div>
+
         <div className="mt-6 pt-6 border-t">
           <div className="flex items-start space-x-3">
             <Checkbox
               id="keepServerRunning"
+              className="mt-[6px]"
               checked={keepServerRunningOnClose}
               onCheckedChange={(checked: boolean) => {
                 setKeepServerRunningOnClose(checked);
@@ -115,6 +153,39 @@ export function ConnectionForm() {
             </div>
           </div>
         </div>
+
+        {platform.metadata.isTauri && (
+          <div className="mt-6 pt-6 border-t">
+            <div className="flex items-start space-x-3">
+              <Checkbox
+                id="allowNetworkAccess"
+                className="mt-[6px]"
+                checked={mode === 'remote'}
+                onCheckedChange={(checked: boolean) => {
+                  setMode(checked ? 'remote' : 'local');
+                  toast({
+                    title: 'Setting updated',
+                    description: checked
+                      ? 'Network access enabled. Restart the app to apply.'
+                      : 'Network access disabled. Restart the app to apply.',
+                  });
+                }}
+              />
+              <div className="space-y-1">
+                <label
+                  htmlFor="allowNetworkAccess"
+                  className="text-sm font-medium leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70 cursor-pointer"
+                >
+                  Allow network access
+                </label>
+                <p className="text-sm text-muted-foreground">
+                  Makes the server accessible from other devices on your network. Restart the app
+                  after changing this setting.
+                </p>
+              </div>
+            </div>
+          </div>
+        )}
       </CardContent>
     </Card>
   );

app/src/components/ServerSettings/GenerationSettings.tsx

@@ -0,0 +1,116 @@
+import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card';
+import { Checkbox } from '@/components/ui/checkbox';
+import { Slider } from '@/components/ui/slider';
+import { useServerStore } from '@/stores/serverStore';
+
+export function GenerationSettings() {
+  const maxChunkChars = useServerStore((state) => state.maxChunkChars);
+  const setMaxChunkChars = useServerStore((state) => state.setMaxChunkChars);
+  const crossfadeMs = useServerStore((state) => state.crossfadeMs);
+  const setCrossfadeMs = useServerStore((state) => state.setCrossfadeMs);
+  const normalizeAudio = useServerStore((state) => state.normalizeAudio);
+  const setNormalizeAudio = useServerStore((state) => state.setNormalizeAudio);
+  const autoplayOnGenerate = useServerStore((state) => state.autoplayOnGenerate);
+  const setAutoplayOnGenerate = useServerStore((state) => state.setAutoplayOnGenerate);
+
+  return (
+    <Card role="region" aria-label="Generation Settings" tabIndex={0}>
+      <CardHeader>
+        <CardTitle>Generation Settings</CardTitle>
+        <CardDescription>
+          Controls for long text generation. These settings apply to all engines.
+        </CardDescription>
+      </CardHeader>
+      <CardContent>
+        <div className="space-y-6">
+          <div className="space-y-3">
+            <div className="flex items-center justify-between">
+              <label htmlFor="maxChunkChars" className="text-sm font-medium leading-none">
+                Auto-chunking limit
+              </label>
+              <span className="text-sm tabular-nums text-muted-foreground">
+                {maxChunkChars} chars
+              </span>
+            </div>
+            <Slider
+              id="maxChunkChars"
+              value={[maxChunkChars]}
+              onValueChange={([value]) => setMaxChunkChars(value)}
+              min={100}
+              max={5000}
+              step={50}
+              aria-label="Auto-chunking character limit"
+            />
+            <p className="text-sm text-muted-foreground">
+              Long text is split into chunks at sentence boundaries before generating. Lower values
+              can improve quality for long outputs.
+            </p>
+          </div>
+
+          <div className="space-y-3">
+            <div className="flex items-center justify-between">
+              <label htmlFor="crossfadeMs" className="text-sm font-medium leading-none">
+                Chunk crossfade
+              </label>
+              <span className="text-sm tabular-nums text-muted-foreground">
+                {crossfadeMs === 0 ? 'Cut' : `${crossfadeMs}ms`}
+              </span>
+            </div>
+            <Slider
+              id="crossfadeMs"
+              value={[crossfadeMs]}
+              onValueChange={([value]) => setCrossfadeMs(value)}
+              min={0}
+              max={200}
+              step={10}
+              aria-label="Chunk crossfade duration"
+            />
+            <p className="text-sm text-muted-foreground">
+              Blends audio between chunks to smooth transitions. Set to 0 for a hard cut.
+            </p>
+          </div>
+
+          <div className="flex items-start gap-3">
+            <Checkbox
+              id="normalizeAudio"
+              checked={normalizeAudio}
+              onCheckedChange={setNormalizeAudio}
+              className="mt-[6px]"
+            />
+            <div className="space-y-1">
+              <label
+                htmlFor="normalizeAudio"
+                className="text-sm font-medium leading-none cursor-pointer"
+              >
+                Normalize audio
+              </label>
+              <p className="text-sm text-muted-foreground">
+                Adjusts output volume to a consistent level across generations.
+              </p>
+            </div>
+          </div>
+
+          <div className="flex items-start gap-3">
+            <Checkbox
+              id="autoplayOnGenerate"
+              checked={autoplayOnGenerate}
+              onCheckedChange={setAutoplayOnGenerate}
+              className="mt-[6px]"
+            />
+            <div className="space-y-1">
+              <label
+                htmlFor="autoplayOnGenerate"
+                className="text-sm font-medium leading-none cursor-pointer"
+              >
+                Autoplay on generate
+              </label>
+              <p className="text-sm text-muted-foreground">
+                Automatically play audio when a generation completes.
+              </p>
+            </div>
+          </div>
+        </div>
+      </CardContent>
+    </Card>
+  );
+}

app/src/components/ServerSettings/GpuAcceleration.tsx

@@ -0,0 +1,366 @@
+import { useQuery, useQueryClient } from '@tanstack/react-query';
+import { AlertCircle, Download, Loader2, RotateCw, Trash2 } from 'lucide-react';
+import { useCallback, useEffect, useRef, useState } from 'react';
+import { Button } from '@/components/ui/button';
+import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
+import { Progress } from '@/components/ui/progress';
+import { apiClient } from '@/lib/api/client';
+import type { CudaDownloadProgress } from '@/lib/api/types';
+import { useServerHealth } from '@/lib/hooks/useServer';
+import { usePlatform } from '@/platform/PlatformContext';
+import { useServerStore } from '@/stores/serverStore';
+
+type RestartPhase = 'idle' | 'stopping' | 'waiting' | 'ready';
+
+export function GpuAcceleration() {
+  const platform = usePlatform();
+  const queryClient = useQueryClient();
+  const serverUrl = useServerStore((state) => state.serverUrl);
+  const { data: health } = useServerHealth();
+
+  const [restartPhase, setRestartPhase] = useState<RestartPhase>('idle');
+  const [error, setError] = useState<string | null>(null);
+  const [downloadProgress, setDownloadProgress] = useState<CudaDownloadProgress | null>(null);
+  const healthPollRef = useRef<ReturnType<typeof setInterval> | null>(null);
+
+  // Query CUDA backend status
+  const {
+    data: cudaStatus,
+    isLoading: cudaStatusLoading,
+    refetch: refetchCudaStatus,
+  } = useQuery({
+    queryKey: ['cuda-status', serverUrl],
+    queryFn: () => apiClient.getCudaStatus(),
+    refetchInterval: (query) => (query.state.status === 'pending' ? false : 10000),
+    retry: 1,
+    enabled: !!health, // Only fetch when backend is reachable
+  });
+
+  // Derived state
+  const isCurrentlyCuda = health?.backend_variant === 'cuda';
+  const cudaAvailable = cudaStatus?.available ?? false;
+  const cudaDownloading = cudaStatus?.downloading ?? false;
+
+  // Clean up health poll on unmount
+  useEffect(() => {
+    return () => {
+      if (healthPollRef.current) {
+        clearInterval(healthPollRef.current);
+        healthPollRef.current = null;
+      }
+    };
+  }, []);
+
+  // SSE progress tracking during download
+  useEffect(() => {
+    if (!cudaDownloading || !serverUrl) {
+      return;
+    }
+
+    const eventSource = new EventSource(`${serverUrl}/backend/cuda-progress`);
+
+    eventSource.onmessage = (event) => {
+      try {
+        const data = JSON.parse(event.data) as CudaDownloadProgress;
+        setDownloadProgress(data);
+
+        if (data.status === 'complete') {
+          eventSource.close();
+          setDownloadProgress(null);
+          refetchCudaStatus();
+        } else if (data.status === 'error') {
+          eventSource.close();
+          setError(data.error || 'Download failed');
+          setDownloadProgress(null);
+          refetchCudaStatus();
+        }
+      } catch (e) {
+        console.error('Error parsing CUDA progress event:', e);
+      }
+    };
+
+    eventSource.onerror = () => {
+      eventSource.close();
+    };
+
+    return () => {
+      eventSource.close();
+    };
+  }, [cudaDownloading, serverUrl, refetchCudaStatus]);
+
+  // Start aggressive health polling during restart
+  const startHealthPolling = useCallback(() => {
+    if (healthPollRef.current) return;
+
+    healthPollRef.current = setInterval(async () => {
+      try {
+        const result = await apiClient.getHealth();
+        if (result.status === 'healthy') {
+          // Server is back up
+          if (healthPollRef.current) {
+            clearInterval(healthPollRef.current);
+            healthPollRef.current = null;
+          }
+          setRestartPhase('ready');
+          // Invalidate all queries to refresh UI
+          queryClient.invalidateQueries();
+          // Reset after a moment
+          setTimeout(() => setRestartPhase('idle'), 2000);
+        }
+      } catch {
+        // Server still down, keep polling
+      }
+    }, 1000);
+  }, [queryClient]);
+
+  const handleDownload = async () => {
+    setError(null);
+    try {
+      await apiClient.downloadCudaBackend();
+      refetchCudaStatus();
+    } catch (e: unknown) {
+      const msg = e instanceof Error ? e.message : 'Failed to start download';
+      if (msg.includes('already downloaded')) {
+        refetchCudaStatus();
+      } else {
+        setError(msg);
+      }
+    }
+  };
+
+  const handleRestart = async () => {
+    setError(null);
+    setRestartPhase('stopping');
+
+    try {
+      setRestartPhase('waiting');
+      startHealthPolling();
+      await platform.lifecycle.restartServer();
+      // Invoke resolved — server is likely ready. Stop polling and refresh.
+      if (healthPollRef.current) {
+        clearInterval(healthPollRef.current);
+        healthPollRef.current = null;
+      }
+      setRestartPhase('ready');
+      queryClient.invalidateQueries();
+      setTimeout(() => setRestartPhase('idle'), 2000);
+    } catch (e: unknown) {
+      setRestartPhase('idle');
+      if (healthPollRef.current) {
+        clearInterval(healthPollRef.current);
+        healthPollRef.current = null;
+      }
+      setError(e instanceof Error ? e.message : 'Restart failed');
+    }
+  };
+
+  const handleSwitchToCpu = async () => {
+    // To switch to CPU: delete the CUDA binary, then restart.
+    // start_server always prefers CUDA if present, so we must remove it first.
+    setError(null);
+    setRestartPhase('stopping');
+
+    try {
+      await apiClient.deleteCudaBackend();
+      setRestartPhase('waiting');
+      startHealthPolling();
+      await platform.lifecycle.restartServer();
+      // Invoke resolved — server is likely ready
+      if (healthPollRef.current) {
+        clearInterval(healthPollRef.current);
+        healthPollRef.current = null;
+      }
+      setRestartPhase('ready');
+      queryClient.invalidateQueries();
+      setTimeout(() => setRestartPhase('idle'), 2000);
+    } catch (e: unknown) {
+      setRestartPhase('idle');
+      if (healthPollRef.current) {
+        clearInterval(healthPollRef.current);
+        healthPollRef.current = null;
+      }
+      setError(e instanceof Error ? e.message : 'Failed to switch to CPU');
+      refetchCudaStatus();
+    }
+  };
+
+  const handleDelete = async () => {
+    setError(null);
+    try {
+      await apiClient.deleteCudaBackend();
+      refetchCudaStatus();
+    } catch (e: unknown) {
+      setError(e instanceof Error ? e.message : 'Failed to delete CUDA backend');
+    }
+  };
+
+  const formatBytes = (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 / k ** i).toFixed(1)} ${sizes[i]}`;
+  };
+
+  // Don't render until health data is available
+  if (!health) return null;
+
+  // If the system already has native GPU (MPS, etc.), only show info - no CUDA needed
+  const hasNativeGpu =
+    health.gpu_available &&
+    !isCurrentlyCuda &&
+    health.gpu_type &&
+    !health.gpu_type.includes('CUDA');
+
+  return (
+    <Card>
+      <CardHeader>
+        <CardTitle>GPU Acceleration</CardTitle>
+      </CardHeader>
+      <CardContent className="space-y-4">
+        {/* Current status */}
+        <div className="space-y-1">
+          <div className="text-sm font-medium">Backend</div>
+          <div className="text-sm text-muted-foreground">
+            {isCurrentlyCuda
+              ? 'CUDA (GPU accelerated)'
+              : hasNativeGpu
+                ? `${health.backend_type === 'mlx' ? 'MLX' : 'PyTorch'} (GPU accelerated)`
+                : 'CPU'}
+          </div>
+        </div>
+
+        {/* GPU info from health */}
+        {health.gpu_type && (
+          <div className="space-y-1">
+            <div className="text-sm font-medium">GPU</div>
+            <div className="text-sm text-muted-foreground">{health.gpu_type}</div>
+            {health.vram_used_mb != null && (
+              <div className="text-xs text-muted-foreground">
+                VRAM: {health.vram_used_mb.toFixed(0)} MB used
+              </div>
+            )}
+          </div>
+        )}
+
+        {/* Native GPU detected - no CUDA download needed */}
+
+        {/* CUDA download section - only show when native GPU is NOT detected (i.e., Windows/Linux NVIDIA users) */}
+        {!hasNativeGpu && (
+          <>
+            {/* Download progress */}
+            {cudaDownloading && downloadProgress && (
+              <div className="space-y-2">
+                <div className="flex items-center justify-between text-sm">
+                  <div className="flex items-center gap-2">
+                    <Loader2 className="h-4 w-4 animate-spin" />
+                    <span>{downloadProgress.filename || 'Downloading CUDA backend...'}</span>
+                  </div>
+                  {downloadProgress.total > 0 && (
+                    <span className="text-muted-foreground">
+                      {downloadProgress.progress.toFixed(1)}%
+                    </span>
+                  )}
+                </div>
+                {downloadProgress.total > 0 && (
+                  <>
+                    <Progress value={downloadProgress.progress} className="h-2" />
+                    <div className="text-xs text-muted-foreground">
+                      {formatBytes(downloadProgress.current)} /{' '}
+                      {formatBytes(downloadProgress.total)}
+                    </div>
+                  </>
+                )}
+              </div>
+            )}
+
+            {/* Restart in progress */}
+            {restartPhase !== 'idle' && (
+              <div className="flex items-center gap-2 p-3 rounded-lg bg-primary/5 border">
+                <Loader2 className="h-4 w-4 animate-spin" />
+                <span className="text-sm">
+                  {restartPhase === 'stopping' && 'Stopping server...'}
+                  {restartPhase === 'waiting' && 'Restarting server...'}
+                  {restartPhase === 'ready' && 'Server restarted successfully!'}
+                </span>
+              </div>
+            )}
+
+            {/* Error display */}
+            {error && (
+              <div className="flex items-center gap-2 text-sm text-destructive">
+                <AlertCircle className="h-4 w-4 shrink-0" />
+                <span>{error}</span>
+              </div>
+            )}
+
+            {/* Actions */}
+            {restartPhase === 'idle' && !cudaDownloading && (
+              <div className="space-y-2">
+                {/* Not downloaded yet - show download button */}
+                {!cudaAvailable && (
+                  <div className="space-y-3">
+                    <p className="text-sm text-muted-foreground">
+                      Download the CUDA backend (~2.4 GB) for NVIDIA GPU acceleration. Requires an
+                      NVIDIA GPU with CUDA support.
+                    </p>
+                    <Button onClick={handleDownload} className="w-full" size="sm">
+                      <Download className="h-4 w-4 mr-2" />
+                      Download CUDA Backend
+                    </Button>
+                  </div>
+                )}
+
+                {/* Downloaded but not active - show switch button */}
+                {cudaAvailable && !isCurrentlyCuda && platform.metadata.isTauri && (
+                  <div className="space-y-3">
+                    <p className="text-sm text-muted-foreground">
+                      CUDA backend is downloaded and ready. Restart the server to enable GPU
+                      acceleration.
+                    </p>
+                    <Button onClick={handleRestart} className="w-full" size="sm">
+                      <RotateCw className="h-4 w-4 mr-2" />
+                      Switch to CUDA Backend
+                    </Button>
+                  </div>
+                )}
+
+                {/* Currently active - show switch back to CPU */}
+                {isCurrentlyCuda && platform.metadata.isTauri && (
+                  <div className="space-y-3">
+                    <p className="text-sm text-muted-foreground">
+                      Running with CUDA GPU acceleration. Switch back to CPU if needed (you can
+                      re-download later).
+                    </p>
+                    <Button
+                      onClick={handleSwitchToCpu}
+                      variant="outline"
+                      className="w-full"
+                      size="sm"
+                    >
+                      <RotateCw className="h-4 w-4 mr-2" />
+                      Switch to CPU Backend
+                    </Button>
+                  </div>
+                )}
+
+                {/* Delete option when downloaded (and not active) */}
+                {cudaAvailable && !isCurrentlyCuda && (
+                  <Button
+                    onClick={handleDelete}
+                    variant="ghost"
+                    className="w-full text-muted-foreground hover:text-destructive"
+                    size="sm"
+                  >
+                    <Trash2 className="h-4 w-4 mr-2" />
+                    Remove CUDA Backend
+                  </Button>
+                )}
+              </div>
+            )}
+          </>
+        )}
+      </CardContent>
+    </Card>
+  );
+}

app/src/components/ServerSettings/ModelProgress.tsx

@@ -8,14 +8,23 @@ 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 +36,7 @@ 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 +45,15 @@ 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 (

app/src/components/ServerSettings/ServerStatus.tsx

@@ -3,14 +3,13 @@ import { Badge } from '@/components/ui/badge';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { useServerHealth } from '@/lib/hooks/useServer';
 import { useServerStore } from '@/stores/serverStore';
-import { ModelProgress } from './ModelProgress';
 
 export function ServerStatus() {
   const { data: health, isLoading, error } = useServerHealth();
   const serverUrl = useServerStore((state) => state.serverUrl);
 
   return (
-    <Card>
+    <Card role="region" aria-label="Server Status" tabIndex={0}>
       <CardHeader>
         <CardTitle>Server Status</CardTitle>
       </CardHeader>
@@ -20,16 +19,6 @@ export function ServerStatus() {
           <div className="font-mono text-sm">{serverUrl}</div>
         </div>
 
-        {/* Model download progress */}
-        <div className="space-y-2">
-          <ModelProgress modelName="qwen-tts-1.7B" displayName="Qwen TTS 1.7B" />
-          <ModelProgress modelName="qwen-tts-0.6B" displayName="Qwen TTS 0.6B" />
-          <ModelProgress modelName="whisper-base" displayName="Whisper Base" />
-          <ModelProgress modelName="whisper-small" displayName="Whisper Small" />
-          <ModelProgress modelName="whisper-medium" displayName="Whisper Medium" />
-          <ModelProgress modelName="whisper-large" displayName="Whisper Large" />
-        </div>
-
         {isLoading ? (
           <div className="flex items-center gap-2">
             <Loader2 className="h-4 w-4 animate-spin" />

app/src/components/ServerSettings/UpdateStatus.tsx

@@ -13,13 +13,18 @@ export function UpdateStatus() {
   const [currentVersion, setCurrentVersion] = useState<string>('');
 
   useEffect(() => {
-    platform.metadata.getVersion()
+    platform.metadata
+      .getVersion()
       .then(setCurrentVersion)
-      .catch(() => setCurrentVersion('0.1.0'));
+      .catch(() => setCurrentVersion('Unknown'));
   }, [platform]);
 
   return (
-    <Card>
+    <Card
+      role="region"
+      aria-label="App Updates"
+      tabIndex={0}
+    >
       <CardHeader>
         <CardTitle>App Updates</CardTitle>
       </CardHeader>

app/src/components/ServerTab/ServerTab.tsx

@@ -1,17 +1,25 @@
 import { ConnectionForm } from '@/components/ServerSettings/ConnectionForm';
-import { ServerStatus } from '@/components/ServerSettings/ServerStatus';
+import { GenerationSettings } from '@/components/ServerSettings/GenerationSettings';
+import { GpuAcceleration } from '@/components/ServerSettings/GpuAcceleration';
 import { UpdateStatus } from '@/components/ServerSettings/UpdateStatus';
+import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
+import { cn } from '@/lib/utils/cn';
 import { usePlatform } from '@/platform/PlatformContext';
+import { usePlayerStore } from '@/stores/playerStore';
 
 export function ServerTab() {
   const platform = usePlatform();
+  const isPlayerVisible = !!usePlayerStore((state) => state.audioUrl);
   return (
-    <div className="space-y-4 overflow-y-auto flex flex-col">
+    <div
+      className={cn('overflow-y-auto flex flex-col', isPlayerVisible && BOTTOM_SAFE_AREA_PADDING)}
+    >
       <div className="grid gap-4 md:grid-cols-2">
         <ConnectionForm />
-        <ServerStatus />
+        <GenerationSettings />
+        {platform.metadata.isTauri && <GpuAcceleration />}
+        {platform.metadata.isTauri && <UpdateStatus />}
       </div>
-      {platform.metadata.isTauri && <UpdateStatus />}
       <div className="py-8 text-center text-sm text-muted-foreground">
         Created by{' '}
         <a

app/src/components/Sidebar.tsx

@@ -1,9 +1,9 @@
 import { Link, useMatchRoute } from '@tanstack/react-router';
-import { Box, BookOpen, Loader2, Mic, Server, Speaker, Volume2 } from 'lucide-react';
+import { BookOpen, Box, 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';
 import { usePlayerStore } from '@/stores/playerStore';
+import { version } from '../../package.json';
 
 interface SidebarProps {
   isMacOS?: boolean;
@@ -19,10 +19,8 @@ const tabs = [
 ];
 
 export function Sidebar({ isMacOS }: SidebarProps) {
-  const isGenerating = useGenerationStore((state) => state.isGenerating);
-  const audioUrl = usePlayerStore((state) => state.audioUrl);
-  const isPlayerVisible = !!audioUrl;
   const matchRoute = useMatchRoute();
+  const isPlayerOpen = !!usePlayerStore((s) => s.audioUrl);
 
   return (
     <div
@@ -42,9 +40,7 @@ export function Sidebar({ isMacOS }: SidebarProps) {
           const Icon = tab.icon;
           // For index route, use exact match; for others, use default matching
           const isActive =
-            tab.path === '/'
+            tab.path === '/' ? matchRoute({ to: '/', exact: true }) : matchRoute({ to: tab.path });
-              ? matchRoute({ to: '/', exact: true })
-              : matchRoute({ to: tab.path });
 
           return (
             <Link
@@ -64,20 +60,13 @@ export function Sidebar({ isMacOS }: SidebarProps) {
         })}
       </div>
 
-      {/* Spacer to push loader to bottom */}
+      {/* Version */}
-      <div className="flex-1" />
+      <div
-
+        className="mt-auto text-[10px] text-muted-foreground/50 transition-all duration-300"
-      {/* Generation Loader */}
+        style={{ paddingBottom: isPlayerOpen ? '7rem' : undefined }}
-      {isGenerating && (
+      >
-        <div
+        v{version}
-          className={cn(
+      </div>
-            'w-full flex items-center justify-center transition-all duration-200',
-            isPlayerVisible ? 'mb-[120px]' : 'mb-0',
-          )}
-        >
-          <Loader2 className="h-6 w-6 text-accent animate-spin" />
-        </div>
-      )}
     </div>
   );
 }

app/src/components/StoriesTab/StoriesTab.tsx

@@ -1,8 +1,11 @@
 import { FloatingGenerateBox } from '@/components/Generation/FloatingGenerateBox';
+import { usePlayerStore } from '@/stores/playerStore';
 import { StoryContent } from './StoryContent';
 import { StoryList } from './StoryList';
 
 export function StoriesTab() {
+  const audioUrl = usePlayerStore((state) => state.audioUrl);
+
   return (
     <div className="flex flex-col h-full min-h-0 overflow-hidden">
       {/* Main content area */}
@@ -18,7 +21,7 @@ export function StoriesTab() {
         </div>
 
         {/* Floating Generate Box - position is managed via storyStore.trackEditorHeight */}
-        <FloatingGenerateBox showVoiceSelector />
+        <FloatingGenerateBox showVoiceSelector isPlayerOpen={!!audioUrl} />
       </div>
     </div>
   );

app/src/components/StoriesTab/StoryContent.tsx

@@ -13,8 +13,11 @@ import {
   sortableKeyboardCoordinates,
   verticalListSortingStrategy,
 } from '@dnd-kit/sortable';
+import { Link } from '@tanstack/react-router';
+import { AnimatePresence, motion } from 'framer-motion';
 import { Download, Plus } from 'lucide-react';
 import { useEffect, useMemo, useRef, useState } from 'react';
+import Loader from 'react-loaders';
 import { Button } from '@/components/ui/button';
 import { Input } from '@/components/ui/input';
 import { Popover, PopoverContent, PopoverTrigger } from '@/components/ui/popover';
@@ -28,6 +31,7 @@ import {
   useStory,
 } from '@/lib/hooks/useStories';
 import { useStoryPlayback } from '@/lib/hooks/useStoryPlayback';
+import { useGenerationStore } from '@/stores/generationStore';
 import { useStoryStore } from '@/stores/storyStore';
 import { SortableStoryChatItem } from './StoryChatItem';
 
@@ -40,6 +44,7 @@ export function StoryContent() {
   const addStoryItem = useAddStoryItem();
   const { toast } = useToast();
   const scrollRef = useRef<HTMLDivElement>(null);
+  const pendingCount = useGenerationStore((s) => s.pendingGenerationIds.size);
 
   // Add generation popover state
   const [searchQuery, setSearchQuery] = useState('');
@@ -53,9 +58,9 @@ export function StoryContent() {
     const query = searchQuery.toLowerCase();
     return historyData.items.filter(
       (gen) =>
+        gen.status === 'completed' &&
         !storyGenerationIds.has(gen.id) &&
-        (gen.text.toLowerCase().includes(query) ||
+        (gen.text.toLowerCase().includes(query) || gen.profile_name.toLowerCase().includes(query)),
-          gen.profile_name.toLowerCase().includes(query)),
     );
   }, [historyData, story, searchQuery]);
 
@@ -267,7 +272,31 @@ export function StoryContent() {
             <p className="text-sm text-muted-foreground mt-1">{story.description}</p>
           )}
         </div>
-        <div className="flex gap-2">
+        <div className="flex gap-2 items-center">
+          <AnimatePresence>
+            {pendingCount > 0 && (
+              <motion.div
+                initial={{ opacity: 0, scale: 0.9, width: 0 }}
+                animate={{ opacity: 1, scale: 1, width: 'auto' }}
+                exit={{ opacity: 0, scale: 0.9, width: 0 }}
+                transition={{ duration: 0.2 }}
+              >
+                <Link
+                  to="/"
+                  className="flex items-center gap-2 h-8 pl-1.5 pr-3 rounded-full bg-card border border-border hover:bg-muted/50 transition-all duration-200 cursor-pointer"
+                >
+                  <div className="shrink-0 w-10 h-5 overflow-hidden flex items-center justify-center">
+                    <div className="scale-[0.45]">
+                      <Loader type="line-scale" active />
+                    </div>
+                  </div>
+                  <span className="text-xs text-muted-foreground whitespace-nowrap">
+                    Generating {pendingCount} {pendingCount === 1 ? 'audio' : 'audios'}
+                  </span>
+                </Link>
+              </motion.div>
+            )}
+          </AnimatePresence>
           <Popover open={isAddOpen} onOpenChange={setIsAddOpen}>
             <PopoverTrigger asChild>
               <Button variant="outline" size="sm">
@@ -287,9 +316,7 @@ export function StoryContent() {
               <div className="max-h-60 overflow-y-auto">
                 {availableGenerations.length === 0 ? (
                   <div className="p-4 text-center text-sm text-muted-foreground">
-                    {searchQuery
+                    {searchQuery ? 'No matching generations found' : 'No available generations'}
-                      ? 'No matching generations found'
-                      : 'No available generations'}
                   </div>
                 ) : (
                   availableGenerations.map((gen) => (

app/src/components/StoriesTab/StoryList.tsx

@@ -194,17 +194,29 @@ export function StoryList() {
           storyList.map((story) => (
             <div
               key={story.id}
+              role="button"
+              tabIndex={0}
               className={cn(
-                'h-24 p-4 border rounded-2xl transition-colors group flex items-center',
+                'h-24 p-4 border rounded-2xl transition-colors group flex items-center cursor-pointer',
                 selectedStoryId === story.id && 'bg-muted border-primary',
               )}
+              aria-label={
+                selectedStoryId === story.id
+                  ? `Story ${story.name}, ${story.item_count} ${story.item_count === 1 ? 'item' : 'items'}, ${formatDate(story.updated_at)}. Selected. Press Enter to select.`
+                  : `Story ${story.name}, ${story.item_count} ${story.item_count === 1 ? 'item' : 'items'}, ${formatDate(story.updated_at)}. Press Enter to select.`
+              }
+              aria-pressed={selectedStoryId === story.id}
+              onClick={() => setSelectedStoryId(story.id)}
+              onKeyDown={(e) => {
+                if (e.target !== e.currentTarget) return;
+                if (e.key === 'Enter' || e.key === ' ') {
+                  e.preventDefault();
+                  setSelectedStoryId(story.id);
+                }
+              }}
             >
               <div className="flex items-start justify-between gap-2 w-full min-w-0">
-                <button
+                <div className="flex-1 min-w-0 text-left overflow-hidden">
-                  type="button"
-                  className="flex-1 min-w-0 text-left cursor-pointer overflow-hidden"
-                  onClick={() => setSelectedStoryId(story.id)}
-                >
                   <h3 className="font-medium truncate">{story.name}</h3>
                   {story.description && (
                     <p className="text-sm text-muted-foreground mt-1 truncate">
@@ -218,7 +230,7 @@ export function StoryList() {
                     <span>•</span>
                     <span>{formatDate(story.updated_at)}</span>
                   </div>
-                </button>
+                </div>
                 <DropdownMenu>
                   <DropdownMenuTrigger asChild>
                     <Button
@@ -226,6 +238,7 @@ export function StoryList() {
                       size="icon"
                       className="h-8 w-8 opacity-0 group-hover:opacity-100 transition-opacity"
                       onClick={(e) => e.stopPropagation()}
+                      aria-label={`Actions for ${story.name}`}
                     >
                       <MoreHorizontal className="h-4 w-4" />
                     </Button>

app/src/components/StoriesTab/StoryTrackEditor.tsx

@@ -736,6 +736,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
               className="h-7 w-7"
               onClick={handlePlayPause}
               title="Play/Pause (Space)"
+              aria-label={isCurrentlyPlaying ? 'Pause' : 'Play'}
             >
               {isCurrentlyPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
             </Button>
@@ -745,6 +746,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
               className="h-7 w-7"
               onClick={handleStop}
               disabled={!isCurrentlyPlaying}
+              aria-label="Stop"
             >
               <Square className="h-3 w-3" />
             </Button>
@@ -762,6 +764,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
                 className="h-7 w-7"
                 onClick={handleSplit}
                 title="Split at playhead (S)"
+                aria-label="Split at playhead"
               >
                 <Scissors className="h-4 w-4" />
               </Button>
@@ -771,6 +774,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
                 className="h-7 w-7"
                 onClick={handleDuplicate}
                 title="Duplicate (Cmd/Ctrl+D)"
+                aria-label="Duplicate clip"
               >
                 <Copy className="h-4 w-4" />
               </Button>
@@ -780,6 +784,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
                 className="h-7 w-7"
                 onClick={handleDelete}
                 title="Delete (Delete/Backspace)"
+                aria-label="Delete clip"
               >
                 <Trash2 className="h-4 w-4" />
               </Button>
@@ -789,10 +794,22 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
           {/* Zoom controls - right side */}
           <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}>
+            <Button
+              variant="ghost"
+              size="icon"
+              className="h-6 w-6"
+              onClick={handleZoomOut}
+              aria-label="Zoom out"
+            >
               <Minus className="h-3 w-3" />
             </Button>
-            <Button variant="ghost" size="icon" className="h-6 w-6" onClick={handleZoomIn}>
+            <Button
+              variant="ghost"
+              size="icon"
+              className="h-6 w-6"
+              onClick={handleZoomIn}
+              aria-label="Zoom in"
+            >
               <Plus className="h-3 w-3" />
             </Button>
           </div>

app/src/components/VoiceProfiles/AudioSampleRecording.tsx

@@ -58,6 +58,7 @@ export function AudioSampleRecording({
   // Request microphone access when component mounts
   useEffect(() => {
     if (!showWaveform) return;
+    if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) return;
 
     let stream: MediaStream | null = null;
 
@@ -139,7 +140,13 @@ export function AudioSampleRecording({
               </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}>
+                <Button
+                  type="button"
+                  size="icon"
+                  variant="outline"
+                  onClick={onPlayPause}
+                  aria-label={isPlaying ? 'Pause' : 'Play'}
+                >
                   {isPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
                 </Button>
                 <Button

app/src/components/VoiceProfiles/AudioSampleSystem.tsx

@@ -77,7 +77,13 @@ export function AudioSampleSystem({
               </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}>
+                <Button
+                  type="button"
+                  size="icon"
+                  variant="outline"
+                  onClick={onPlayPause}
+                  aria-label={isPlaying ? 'Pause' : 'Play'}
+                >
                   {isPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
                 </Button>
                 <Button

app/src/components/VoiceProfiles/AudioSampleUpload.tsx

@@ -110,6 +110,7 @@ export function AudioSampleUpload({
                     variant="outline"
                     onClick={onPlayPause}
                     disabled={isValidating}
+                    aria-label={isPlaying ? 'Pause' : 'Play'}
                   >
                     {isPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
                   </Button>

app/src/components/VoiceProfiles/ProfileCard.tsx

@@ -61,14 +61,32 @@ export function ProfileCard({ profile }: ProfileCardProps) {
     exportProfile.mutate(profile.id);
   };
 
+  const handleKeyDown = (e: React.KeyboardEvent) => {
+    const target = e.target as HTMLElement;
+    if (target.closest('button')) return;
+    if (e.key === 'Enter' || e.key === ' ') {
+      e.preventDefault();
+      handleSelect();
+    }
+  };
+
+  const selectLabel = isSelected
+    ? `${profile.name}, ${profile.language}. Selected as voice for generation.`
+    : `${profile.name}, ${profile.language}. Select as voice for generation.`;
+
   return (
     <>
       <Card
         className={cn(
-          'cursor-pointer hover:shadow-md transition-all flex flex-col',
+          'cursor-pointer hover:shadow-md transition-all flex flex-col h-[162px]',
           isSelected && 'ring-2 ring-primary shadow-md',
         )}
         onClick={handleSelect}
+        tabIndex={0}
+        role="button"
+        aria-label={selectLabel}
+        aria-pressed={isSelected}
+        onKeyDown={handleKeyDown}
       >
         <CardHeader className="p-3 pb-2">
           <CardTitle className="flex items-center gap-1.5 text-base font-medium">

app/src/components/VoiceProfiles/ProfileForm.tsx

@@ -43,7 +43,7 @@ import {
 } from '@/lib/hooks/useProfiles';
 import { useSystemAudioCapture } from '@/lib/hooks/useSystemAudioCapture';
 import { useTranscription } from '@/lib/hooks/useTranscription';
-import { formatAudioDuration, getAudioDuration } from '@/lib/utils/audio';
+import { convertToWav, formatAudioDuration, getAudioDuration } from '@/lib/utils/audio';
 import { usePlatform } from '@/platform/PlatformContext';
 import { useServerStore } from '@/stores/serverStore';
 import { type ProfileFormDraft, useUIStore } from '@/stores/uiStore';
@@ -505,10 +505,23 @@ export function ProfileForm() {
           language: data.language,
         });
 
+        // Convert non-WAV uploads to WAV so the backend can always use soundfile.
+        // Recorded audio is already WAV (from useAudioRecording's convertToWav call).
+        let fileToUpload: File = sampleFile;
+        if (!sampleFile.type.includes('wav') && !sampleFile.name.toLowerCase().endsWith('.wav')) {
+          try {
+            const wavBlob = await convertToWav(sampleFile);
+            const wavName = sampleFile.name.replace(/\.[^.]+$/, '.wav');
+            fileToUpload = new File([wavBlob], wavName, { type: 'audio/wav' });
+          } catch {
+            // If browser can't decode the format, send the original and let the backend try.
+          }
+        }
+
         try {
           await addSample.mutateAsync({
             profileId: profile.id,
-            file: sampleFile,
+            file: fileToUpload,
             referenceText: referenceText,
           });
 

app/src/components/VoiceProfiles/ProfileList.tsx

@@ -41,9 +41,11 @@ export function ProfileList() {
             </CardContent>
           </Card>
         ) : (
-          <div className="grid gap-4 grid-cols-3 auto-rows-auto p-1 pb-[150px]">
+          <div className="flex gap-4 overflow-x-auto p-1 pb-1 lg:grid lg:grid-cols-3 lg:auto-rows-auto lg:overflow-x-visible lg:pb-[150px]">
             {allProfiles.map((profile) => (
-              <ProfileCard key={profile.id} profile={profile} />
+              <div key={profile.id} className="shrink-0 w-[200px] lg:w-auto lg:shrink">
+                <ProfileCard profile={profile} />
+              </div>
             ))}
           </div>
         )}

app/src/components/VoiceProfiles/SampleList.tsx

@@ -102,6 +102,7 @@ function MiniSamplePlayer({ audioUrl }: MiniSamplePlayerProps) {
           className="h-7 w-7 shrink-0"
           onClick={handlePlayPause}
           disabled={isLoading}
+          aria-label={isPlaying ? 'Pause sample' : 'Play sample'}
         >
           {isPlaying ? <Pause className="h-3.5 w-3.5" /> : <Play className="h-3.5 w-3.5 ml-0.5" />}
         </Button>
@@ -113,6 +114,8 @@ function MiniSamplePlayer({ audioUrl }: MiniSamplePlayerProps) {
             max={100}
             step={0.1}
             className="flex-1"
+            aria-label="Sample playback position"
+            aria-valuetext={`${formatAudioDuration(currentTime)} of ${formatAudioDuration(duration)}`}
           />
           <div className="flex items-center gap-1 text-xs text-muted-foreground shrink-0 min-w-[70px]">
             <span className="font-mono">{formatAudioDuration(currentTime)}</span>
@@ -128,6 +131,7 @@ function MiniSamplePlayer({ audioUrl }: MiniSamplePlayerProps) {
           className="h-7 w-7 shrink-0"
           onClick={handleStop}
           title="Stop"
+          aria-label="Stop playback"
         >
           <X className="h-3.5 w-3.5" />
         </Button>

app/src/components/VoicesTab/VoicesTab.tsx

@@ -79,8 +79,8 @@ export function VoicesTab() {
     setDialogOpen(true);
   };
 
-  const handleDelete = (profileId: string) => {
+  const handleProfileDelete = async (profileId: string) => {
-    if (confirm('Are you sure you want to delete this profile?')) {
+    if (await confirm('Are you sure you want to delete this profile?')) {
       deleteProfile.mutate(profileId);
     }
   };
@@ -147,7 +147,7 @@ export function VoicesTab() {
                 channels={channels || []}
                 onChannelChange={(channelIds) => handleChannelChange(profile.id, channelIds)}
                 onEdit={() => handleEdit(profile.id)}
-                onDelete={() => handleDelete(profile.id)}
+                onDelete={() => handleProfileDelete(profile.id)}
               />
             ))}
           </TableBody>
@@ -179,25 +179,36 @@ function VoiceRow({
   onDelete,
 }: VoiceRowProps) {
   const { data: samples } = useProfileSamples(profile.id);
+  const sampleCount = samples?.length || 0;
+
+  const rowLabel = `${profile.name}, ${profile.language}, ${generationCount} generations, ${sampleCount} samples. Press Enter to edit.`;
 
   return (
     <TableRow className="cursor-pointer" onClick={onEdit}>
       <TableCell>
-        <div className="flex items-center gap-2">
+        <button
+          type="button"
+          className="flex w-full min-w-0 items-center gap-2 text-left focus:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 rounded"
+          aria-label={rowLabel}
+          onClick={(e) => {
+            e.stopPropagation();
+            onEdit();
+          }}
+        >
           <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>
-          <div>
+          <div className="min-w-0">
-            <div className="font-medium">{profile.name}</div>
+            <div className="font-medium truncate">{profile.name}</div>
             {profile.description && (
-              <div className="text-sm text-muted-foreground">{profile.description}</div>
+              <div className="text-sm text-muted-foreground truncate">{profile.description}</div>
             )}
           </div>
-        </div>
+        </button>
       </TableCell>
       <TableCell onClick={(e) => e.stopPropagation()}>{profile.language}</TableCell>
       <TableCell onClick={(e) => e.stopPropagation()}>{generationCount}</TableCell>
-      <TableCell onClick={(e) => e.stopPropagation()}>{samples?.length || 0}</TableCell>
+      <TableCell onClick={(e) => e.stopPropagation()}>{sampleCount}</TableCell>
       <TableCell onClick={(e) => e.stopPropagation()}>
         <MultiSelect
           options={channels.map((ch) => ({
@@ -213,7 +224,7 @@ function VoiceRow({
       <TableCell onClick={(e) => e.stopPropagation()}>
         <DropdownMenu>
           <DropdownMenuTrigger asChild>
-            <Button variant="ghost" size="icon">
+            <Button variant="ghost" size="icon" aria-label={`Actions for ${profile.name}`}>
               <MoreHorizontal className="h-4 w-4" />
             </Button>
           </DropdownMenuTrigger>

app/src/components/ui/checkbox.tsx

@@ -1,5 +1,5 @@
-import * as React from 'react';
 import { Check } from 'lucide-react';
+import * as React from 'react';
 import { cn } from '@/lib/utils/cn';
 
 export interface CheckboxProps {

app/src/hooks/useAutoUpdater.ts

@@ -1,4 +1,4 @@
-import { useCallback, useEffect, useState } from 'react';
+import { useCallback, useEffect, useRef, useState } from 'react';
 import { usePlatform } from '@/platform/PlatformContext';
 import type { UpdateStatus } from '@/platform/types';
 
@@ -7,9 +7,8 @@ export type { UpdateStatus };
 
 export function useAutoUpdater(checkOnMount = false) {
   const platform = usePlatform();
-  const [status, setStatus] = useState<UpdateStatus>(
+  const [status, setStatus] = useState<UpdateStatus>(platform.updater.getStatus());
-    platform.updater.getStatus(),
+  const hasCheckedRef = useRef(false);
-  );
 
   // Subscribe to updater status changes
   useEffect(() => {
@@ -17,25 +16,32 @@ export function useAutoUpdater(checkOnMount = false) {
       setStatus(newStatus);
     });
     return unsubscribe;
-  }, [platform]);
+    // 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();
-  }, [platform]);
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.checkForUpdates]);
 
   const downloadAndInstall = useCallback(async () => {
     await platform.updater.downloadAndInstall();
-  }, [platform]);
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.downloadAndInstall]);
 
   const restartAndInstall = useCallback(async () => {
     await platform.updater.restartAndInstall();
-  }, [platform]);
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.restartAndInstall]);
 
   useEffect(() => {
-    if (checkOnMount && platform.metadata.isTauri) {
+    if (checkOnMount && platform.metadata.isTauri && !hasCheckedRef.current) {
+      hasCheckedRef.current = true;
       checkForUpdates();
     }
-  }, [checkOnMount, checkForUpdates, platform.metadata.isTauri]);
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.metadata.isTauricheckOnMountcheckForUpdates]);
 
   return {
     status,

app/src/hooks/useAutoUpdater.tsx

@@ -0,0 +1,209 @@
+import { Download, RefreshCw } from 'lucide-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.isTauricheckOnMountcheckForUpdates]);
+
+  // 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">
+          <Download 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}>
+          <RefreshCw 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,
+  };
+}

app/src/index.css

@@ -1,4 +1,5 @@
 @import "tailwindcss" source(".");
+@import "loaders.css/loaders.min.css";
 
 @theme {
   --radius-sm: calc(var(--radius) - 4px);
@@ -155,3 +156,18 @@
   animation: fadeIn 0.5s ease-out 0.15s forwards;
   opacity: 0;
 }
+
+/* react-loaders */
+.line-scale-pulse-out-rapid > div,
+.line-scale > div {
+  background-color: hsl(var(--accent)) !important;
+}
+
+.loader-hidden {
+  display: block;
+}
+
+.loader-hidden > div > div {
+  animation-play-state: paused !important;
+  background-color: hsl(var(--muted-foreground)) !important;
+}

app/src/lib/api/client.ts

@@ -1,29 +1,30 @@
-import { useServerStore } from '@/stores/serverStore';
 import type { LanguageCode } from '@/lib/constants/languages';
+import { useServerStore } from '@/stores/serverStore';
 import type {
-  VoiceProfileCreate,
+  ActiveTasksResponse,
-  VoiceProfileResponse,
+  CudaStatus,
-  ProfileSampleResponse,
   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 {
@@ -199,6 +200,12 @@ class ApiClient {
     });
   }
 
+  async retryGeneration(generationId: string): Promise<GenerationResponse> {
+    return this.request<GenerationResponse>(`/generate/${generationId}/retry`, {
+      method: 'POST',
+    });
+  }
+
   // History
   async listHistory(query?: HistoryQuery): Promise<HistoryListResponse> {
     const params = new URLSearchParams();
@@ -251,7 +258,13 @@ 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);
@@ -271,6 +284,11 @@ class ApiClient {
     return response.json();
   }
 
+  // Generation status SSE
+  getGenerationStatusUrl(generationId: string): string {
+    return `${this.getBaseUrl()}/generate/${generationId}/status`;
+  }
+
   // Audio
   getAudioUrl(audioId: string): string {
     return `${this.getBaseUrl()}/audio/${audioId}`;
@@ -309,11 +327,34 @@ class ApiClient {
     return this.request<ModelStatusListResponse>('/models/status');
   }
 
+  async getModelsCacheDir(): Promise<{ path: string }> {
+    return this.request<{ path: string }>('/models/cache-dir');
+  }
+
+  async migrateModels(destination: string): Promise<{ source: string; destination: string }> {
+    return this.request('/models/migrate', {
+      method: 'POST',
+      body: JSON.stringify({ destination }),
+    });
+  }
+
+  getMigrationProgressUrl(): string {
+    return `${this.getBaseUrl()}/models/migrate/progress`;
+  }
+
   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 }> {
@@ -322,11 +363,28 @@ class ApiClient {
     });
   }
 
+  async unloadModel(modelName: string): Promise<{ message: string }> {
+    return this.request<{ message: string }>(`/models/${modelName}/unload`, {
+      method: 'POST',
+    });
+  }
+
+  async cancelDownload(modelName: string): Promise<{ message: string }> {
+    return this.request<{ message: string }>('/models/download/cancel', {
+      method: 'POST',
+      body: JSON.stringify({ model_name: modelName } as ModelDownloadRequest),
+    });
+  }
+
   // Task Management
   async getActiveTasks(): Promise<ActiveTasksResponse> {
     return this.request<ActiveTasksResponse>('/tasks/active');
   }
 
+  async clearAllTasks(): Promise<{ message: string }> {
+    return this.request<{ message: string }>('/tasks/clear', { method: 'POST' });
+  }
+
   // Audio Channels
   async listChannels(): Promise<
     Array<{
@@ -340,10 +398,7 @@ class ApiClient {
     return this.request('/channels');
   }
 
-  async createChannel(data: {
+  async createChannel(data: { name: string; device_ids: string[] }): Promise<{
-    name: string;
-    device_ids: string[];
-  }): Promise<{
     id: string;
     name: string;
     is_default: boolean;
@@ -385,10 +440,7 @@ class ApiClient {
     return this.request(`/channels/${channelId}/voices`);
   }
 
-  async setChannelVoices(
+  async setChannelVoices(channelId: string, profileIds: string[]): Promise<{ message: string }> {
-    channelId: string,
-    profileIds: string[],
-  ): Promise<{ message: string }> {
     return this.request(`/channels/${channelId}/voices`, {
       method: 'PUT',
       body: JSON.stringify({ profile_ids: profileIds }),
@@ -399,16 +451,30 @@ class ApiClient {
     return this.request(`/profiles/${profileId}/channels`);
   }
 
-  async setProfileChannels(
+  async setProfileChannels(profileId: string, channelIds: string[]): Promise<{ message: string }> {
-    profileId: string,
-    channelIds: string[],
-  ): Promise<{ message: string }> {
     return this.request(`/profiles/${profileId}/channels`, {
       method: 'PUT',
       body: JSON.stringify({ channel_ids: channelIds }),
     });
   }
 
+  // CUDA Backend Management
+  async getCudaStatus(): Promise<CudaStatus> {
+    return this.request<CudaStatus>('/backend/cuda-status');
+  }
+
+  async downloadCudaBackend(): Promise<{ message: string; progress_key: string }> {
+    return this.request<{ message: string; progress_key: string }>('/backend/download-cuda', {
+      method: 'POST',
+    });
+  }
+
+  async deleteCudaBackend(): Promise<{ message: string }> {
+    return this.request<{ message: string }>('/backend/cuda', {
+      method: 'DELETE',
+    });
+  }
+
   // Stories
   async listStories(): Promise<StoryResponse[]> {
     return this.request<StoryResponse[]>('/stories');
@@ -465,21 +531,33 @@ 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),

app/src/lib/api/models/ModelStatus.ts

@@ -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;
 };

app/src/lib/api/types.ts

@@ -34,6 +34,11 @@ export interface GenerationRequest {
   language: LanguageCode;
   seed?: number;
   model_size?: '1.7B' | '0.6B';
+  engine?: 'qwen' | 'luxtts' | 'chatterbox' | 'chatterbox_turbo';
+  instruct?: string;
+  max_chunk_chars?: number;
+  crossfade_ms?: number;
+  normalize?: boolean;
 }
 
 export interface GenerationResponse {
@@ -41,9 +46,14 @@ export interface GenerationResponse {
   profile_id: string;
   text: string;
   language: string;
-  audio_path: string;
+  audio_path?: string;
-  duration: number;
+  duration?: number;
   seed?: number;
+  instruct?: string;
+  engine?: string;
+  model_size?: string;
+  status: 'generating' | 'completed' | 'failed';
+  error?: string;
   created_at: string;
 }
 
@@ -78,7 +88,29 @@ export interface HealthResponse {
   model_downloaded?: boolean;
   model_size?: string;
   gpu_available: boolean;
+  gpu_type?: string;
   vram_used_mb?: number;
+  backend_type?: string;
+  backend_variant?: string; // "cpu" or "cuda"
+}
+
+export interface CudaDownloadProgress {
+  model_name: string;
+  current: number;
+  total: number;
+  progress: number;
+  filename?: string;
+  status: 'downloading' | 'extracting' | 'complete' | 'error';
+  timestamp: string;
+  error?: string;
+}
+
+export interface CudaStatus {
+  available: boolean; // CUDA binary exists on disk
+  active: boolean; // Currently running the CUDA binary
+  binary_path?: string;
+  downloading: boolean; // Download in progress
+  download_progress?: CudaDownloadProgress;
 }
 
 export interface ModelProgress {
@@ -95,11 +127,29 @@ export interface ModelProgress {
 export interface ModelStatus {
   model_name: string;
   display_name: string;
+  hf_repo_id?: string; // HuggingFace repository ID
   downloaded: boolean;
+  downloading: boolean; // True if download is in progress
   size_mb?: number;
   loaded: boolean;
 }
 
+export interface HuggingFaceModelInfo {
+  id: string;
+  author: string;
+  lastModified: string;
+  pipeline_tag?: string;
+  library_name?: string;
+  downloads: number;
+  likes: number;
+  tags: string[];
+  cardData?: {
+    license?: string;
+    language?: string[];
+    pipeline_tag?: string;
+  };
+}
+
 export interface ModelStatusListResponse {
   models: ModelStatus[];
 }
@@ -112,6 +162,11 @@ export interface ActiveDownloadTask {
   model_name: string;
   status: string;
   started_at: string;
+  error?: string;
+  progress?: number; // 0-100 percentage
+  current?: number; // bytes downloaded
+  total?: number; // total bytes
+  filename?: string; // current file being downloaded
 }
 
 export interface ActiveGenerationTask {

app/src/lib/constants/languages.ts

@@ -1,26 +1,86 @@
 /**
- * Supported languages for Qwen3-TTS
+ * Supported languages for voice generation, per engine.
- * Based on: https://github.com/QwenLM/Qwen3-TTS
+ *
+ * Qwen3-TTS supports 10 languages.
+ * LuxTTS is English-only.
+ * Chatterbox Multilingual supports 23 languages.
+ * Chatterbox Turbo is English-only.
  */
 
-export const SUPPORTED_LANGUAGES = {
+/** All languages that any engine supports. */
-  zh: 'Chinese',
+export const ALL_LANGUAGES = {
+  ar: 'Arabic',
+  da: 'Danish',
+  de: 'German',
+  el: 'Greek',
   en: 'English',
+  es: 'Spanish',
+  fi: 'Finnish',
+  fr: 'French',
+  he: 'Hebrew',
+  hi: 'Hindi',
+  it: 'Italian',
   ja: 'Japanese',
   ko: 'Korean',
-  de: 'German',
+  ms: 'Malay',
-  fr: 'French',
+  nl: 'Dutch',
-  ru: 'Russian',
+  no: 'Norwegian',
+  pl: 'Polish',
   pt: 'Portuguese',
-  es: 'Spanish',
+  ru: 'Russian',
-  it: 'Italian',
+  sv: 'Swedish',
+  sw: 'Swahili',
+  tr: 'Turkish',
+  zh: 'Chinese',
 } as const;
 
-export type LanguageCode = keyof typeof SUPPORTED_LANGUAGES;
+export type LanguageCode = keyof typeof ALL_LANGUAGES;
 
-export const LANGUAGE_CODES = Object.keys(SUPPORTED_LANGUAGES) as LanguageCode[];
+/** Per-engine supported language codes. */
+export const ENGINE_LANGUAGES: Record<string, readonly LanguageCode[]> = {
+  qwen: ['zh', 'en', 'ja', 'ko', 'de', 'fr', 'ru', 'pt', 'es', 'it'],
+  luxtts: ['en'],
+  chatterbox: [
+    'ar',
+    'da',
+    'de',
+    'el',
+    'en',
+    'es',
+    'fi',
+    'fr',
+    'he',
+    'hi',
+    'it',
+    'ja',
+    'ko',
+    'ms',
+    'nl',
+    'no',
+    'pl',
+    'pt',
+    'ru',
+    'sv',
+    'sw',
+    'tr',
+    'zh',
+  ],
+  chatterbox_turbo: ['en'],
+} as const;
 
+/** Helper: get language options for a given engine. */
+export function getLanguageOptionsForEngine(engine: string) {
+  const codes = ENGINE_LANGUAGES[engine] ?? ENGINE_LANGUAGES.qwen;
+  return codes.map((code) => ({
+    value: code,
+    label: ALL_LANGUAGES[code],
+  }));
+}
+
+// ── Backwards-compatible exports used elsewhere ──────────────────────
+export const SUPPORTED_LANGUAGES = ALL_LANGUAGES;
+export const LANGUAGE_CODES = Object.keys(ALL_LANGUAGES) as LanguageCode[];
 export const LANGUAGE_OPTIONS = LANGUAGE_CODES.map((code) => ({
   value: code,
-  label: SUPPORTED_LANGUAGES[code],
+  label: ALL_LANGUAGES[code],
 }));

app/src/lib/hooks/useAudioRecording.ts

@@ -20,11 +20,13 @@ export function useAudioRecording({
   const streamRef = useRef<MediaStream | null>(null);
   const timerRef = useRef<number | null>(null);
   const startTimeRef = useRef<number | null>(null);
+  const cancelledRef = useRef<boolean>(false);
 
   const startRecording = useCallback(async () => {
     try {
       setError(null);
       chunksRef.current = [];
+      cancelledRef.current = false;
       setDuration(0);
 
       // Check if getUserMedia is available
@@ -87,31 +89,34 @@ export function useAudioRecording({
       };
 
       mediaRecorder.onstop = async () => {
+        // Snapshot the cancellation flag and recorded duration immediately —
+        // cancelRecording() clears chunks and sets cancelledRef synchronously
+        // before this async handler runs, so we must check it first.
+        const wasCancelled = cancelledRef.current;
+        const recordedDuration = startTimeRef.current
+          ? (Date.now() - startTimeRef.current) / 1000
+          : undefined;
+
         const webmBlob = new Blob(chunksRef.current, { type: 'audio/webm' });
 
-        // Convert to WAV format to avoid needing ffmpeg on backend
+        // Stop all tracks now that we have the data
-        try {
-          const wavBlob = await convertToWav(webmBlob);
-
-          // Pass the actual recorded duration
-          const recordedDuration = startTimeRef.current
-            ? (Date.now() - startTimeRef.current) / 1000
-            : undefined;
-          onRecordingComplete?.(wavBlob, recordedDuration);
-        } catch (err) {
-          console.error('Error converting audio to WAV:', err);
-          // Fallback to original blob if conversion fails
-          const recordedDuration = startTimeRef.current
-            ? (Date.now() - startTimeRef.current) / 1000
-            : undefined;
-          onRecordingComplete?.(webmBlob, recordedDuration);
-        }
-
-        // Stop all tracks
         streamRef.current?.getTracks().forEach((track) => {
           track.stop();
         });
         streamRef.current = null;
+
+        // Don't fire completion callback if the recording was cancelled
+        if (wasCancelled) return;
+
+        // Convert to WAV format to avoid needing ffmpeg on backend
+        try {
+          const wavBlob = await convertToWav(webmBlob);
+          onRecordingComplete?.(wavBlob, recordedDuration);
+        } catch (err) {
+          console.error('Error converting audio to WAV:', err);
+          // Fallback to original blob if conversion fails
+          onRecordingComplete?.(webmBlob, recordedDuration);
+        }
       };
 
       mediaRecorder.onerror = (event) => {
@@ -167,9 +172,10 @@ export function useAudioRecording({
 
   const cancelRecording = useCallback(() => {
     if (mediaRecorderRef.current) {
+      cancelledRef.current = true; // Must be set before stop() triggers onstop
+      chunksRef.current = [];
       mediaRecorderRef.current.stop();
       setIsRecording(false);
-      chunksRef.current = [];
       setDuration(0);
     }
 

app/src/lib/hooks/useGenerationForm.ts

@@ -8,14 +8,15 @@ import { LANGUAGE_CODES, type LanguageCode } from '@/lib/constants/languages';
 import { useGeneration } from '@/lib/hooks/useGeneration';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
 import { useGenerationStore } from '@/stores/generationStore';
-import { usePlayerStore } from '@/stores/playerStore';
+import { useServerStore } from '@/stores/serverStore';
 
 const generationSchema = z.object({
-  text: z.string().min(1, 'Text is required').max(5000),
+  text: z.string().min(1, 'Text is required').max(50000),
   language: z.enum(LANGUAGE_CODES as [LanguageCode, ...LanguageCode[]]),
   seed: z.number().int().optional(),
   modelSize: z.enum(['1.7B', '0.6B']).optional(),
   instruct: z.string().max(500).optional(),
+  engine: z.enum(['qwen', 'luxtts', 'chatterbox', 'chatterbox_turbo']).optional(),
 });
 
 export type GenerationFormValues = z.infer<typeof generationSchema>;
@@ -28,8 +29,10 @@ interface UseGenerationFormOptions {
 export function useGenerationForm(options: UseGenerationFormOptions = {}) {
   const { toast } = useToast();
   const generation = useGeneration();
-  const setAudioWithAutoPlay = usePlayerStore((state) => state.setAudioWithAutoPlay);
+  const addPendingGeneration = useGenerationStore((state) => state.addPendingGeneration);
-  const setIsGenerating = useGenerationStore((state) => state.setIsGenerating);
+  const maxChunkChars = useServerStore((state) => state.maxChunkChars);
+  const crossfadeMs = useServerStore((state) => state.crossfadeMs);
+  const normalizeAudio = useServerStore((state) => state.normalizeAudio);
   const [downloadingModelName, setDownloadingModelName] = useState<string | null>(null);
   const [downloadingDisplayName, setDownloadingDisplayName] = useState<string | null>(null);
 
@@ -47,6 +50,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
       seed: undefined,
       modelSize: '1.7B',
       instruct: '',
+      engine: 'qwen',
       ...options.defaultValues,
     },
   });
@@ -65,11 +69,27 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
     }
 
     try {
-      setIsGenerating(true);
+      const engine = data.engine || 'qwen';
-
+      const modelName =
-      const modelName = `qwen-tts-${data.modelSize}`;
+        engine === 'luxtts'
-      const displayName = data.modelSize === '1.7B' ? 'Qwen TTS 1.7B' : 'Qwen TTS 0.6B';
+          ? 'luxtts'
+          : engine === 'chatterbox'
+            ? 'chatterbox-tts'
+            : engine === 'chatterbox_turbo'
+              ? 'chatterbox-turbo'
+              : `qwen-tts-${data.modelSize}`;
+      const displayName =
+        engine === 'luxtts'
+          ? 'LuxTTS'
+          : engine === 'chatterbox'
+            ? 'Chatterbox TTS'
+            : engine === 'chatterbox_turbo'
+              ? 'Chatterbox Turbo'
+              : data.modelSize === '1.7B'
+                ? 'Qwen TTS 1.7B'
+                : 'Qwen TTS 0.6B';
 
+      // Check if model needs downloading
       try {
         const modelStatus = await apiClient.getModelStatus();
         const model = modelStatus.models.find((m) => m.model_name === modelName);
@@ -82,24 +102,33 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
         console.error('Failed to check model status:', error);
       }
 
+      const isQwen = engine === 'qwen';
+      // This now returns immediately with status="generating"
       const result = await generation.mutateAsync({
         profile_id: selectedProfileId,
         text: data.text,
         language: data.language,
         seed: data.seed,
-        model_size: data.modelSize,
+        model_size: isQwen ? data.modelSize : undefined,
-        instruct: data.instruct || undefined,
+        engine,
+        instruct: isQwen ? data.instruct || undefined : undefined,
+        max_chunk_chars: maxChunkChars,
+        crossfade_ms: crossfadeMs,
+        normalize: normalizeAudio,
       });
 
-      toast({
+      // Track this generation for SSE status updates
-        title: 'Generation complete!',
+      addPendingGeneration(result.id);
-        description: `Audio generated (${result.duration.toFixed(2)}s)`,
+
+      // Reset form immediately — user can start typing again
+      form.reset({
+        text: '',
+        language: data.language,
+        seed: undefined,
+        modelSize: data.modelSize,
+        instruct: '',
+        engine: data.engine,
       });
-
-      const audioUrl = apiClient.getAudioUrl(result.id);
-      setAudioWithAutoPlay(audioUrl, result.id, selectedProfileId, data.text.substring(0, 50));
-
-      form.reset();
       options.onSuccess?.(result.id);
     } catch (error) {
       toast({
@@ -108,7 +137,6 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
         variant: 'destructive',
       });
     } finally {
-      setIsGenerating(false);
       setDownloadingModelName(null);
       setDownloadingDisplayName(null);
     }

app/src/lib/hooks/useGenerationProgress.ts

@@ -0,0 +1,154 @@
+import { useQueryClient } from '@tanstack/react-query';
+import { useEffect, useRef } from 'react';
+import { useToast } from '@/components/ui/use-toast';
+import { apiClient } from '@/lib/api/client';
+import { useGenerationStore } from '@/stores/generationStore';
+import { usePlayerStore } from '@/stores/playerStore';
+import { useServerStore } from '@/stores/serverStore';
+
+interface GenerationStatusEvent {
+  id: string;
+  status: 'generating' | 'completed' | 'failed' | 'not_found';
+  duration?: number;
+  error?: string;
+}
+
+/**
+ * Subscribes to SSE for all pending generations. When a generation completes,
+ * invalidates the history query, removes it from pending, and auto-plays
+ * if the player is idle.
+ */
+export function useGenerationProgress() {
+  const queryClient = useQueryClient();
+  const { toast } = useToast();
+  const pendingIds = useGenerationStore((s) => s.pendingGenerationIds);
+  const removePendingGeneration = useGenerationStore((s) => s.removePendingGeneration);
+  const removePendingStoryAdd = useGenerationStore((s) => s.removePendingStoryAdd);
+  const isPlaying = usePlayerStore((s) => s.isPlaying);
+  const setAudioWithAutoPlay = usePlayerStore((s) => s.setAudioWithAutoPlay);
+  const autoplayOnGenerate = useServerStore((s) => s.autoplayOnGenerate);
+
+  // Keep refs to avoid stale closures in EventSource handlers
+  const isPlayingRef = useRef(isPlaying);
+  const autoplayRef = useRef(autoplayOnGenerate);
+  isPlayingRef.current = isPlaying;
+  autoplayRef.current = autoplayOnGenerate;
+
+  // Track active EventSource instances
+  const eventSourcesRef = useRef<Map<string, EventSource>>(new Map());
+
+  // Unmount-only cleanup — close all SSE connections when the hook is torn down
+  useEffect(() => {
+    const sources = eventSourcesRef.current;
+    return () => {
+      for (const source of sources.values()) {
+        source.close();
+      }
+      sources.clear();
+    };
+  }, []);
+
+  useEffect(() => {
+    const currentSources = eventSourcesRef.current;
+
+    // Close SSE connections for IDs no longer pending
+    for (const [id, source] of currentSources.entries()) {
+      if (!pendingIds.has(id)) {
+        source.close();
+        currentSources.delete(id);
+      }
+    }
+
+    // Open SSE connections for new pending IDs
+    for (const id of pendingIds) {
+      if (currentSources.has(id)) continue;
+
+      const url = apiClient.getGenerationStatusUrl(id);
+      const source = new EventSource(url);
+
+      source.onmessage = (event) => {
+        try {
+          const data: GenerationStatusEvent = JSON.parse(event.data);
+
+          if (data.status === 'completed') {
+            source.close();
+            currentSources.delete(id);
+            removePendingGeneration(id);
+
+            // Refresh history to pick up the completed generation
+            queryClient.invalidateQueries({ queryKey: ['history'] });
+
+            // If this generation was queued for a story, add it now
+            const storyId = removePendingStoryAdd(id);
+            if (storyId) {
+              apiClient
+                .addStoryItem(storyId, { generation_id: id })
+                .then(() => {
+                  queryClient.invalidateQueries({ queryKey: ['stories'] });
+                  queryClient.invalidateQueries({ queryKey: ['stories', storyId] });
+                  toast({
+                    title: 'Added to story',
+                    description: data.duration
+                      ? `Audio generated (${data.duration.toFixed(2)}s) and added to story`
+                      : 'Audio generated and added to story',
+                  });
+                })
+                .catch(() => {
+                  toast({
+                    title: 'Generation complete',
+                    description: 'Audio generated but failed to add to story',
+                    variant: 'destructive',
+                  });
+                });
+            } else {
+              // toast({
+              //   title: 'Generation complete!',
+              //   description: data.duration
+              //     ? `Audio generated (${data.duration.toFixed(2)}s)`
+              //     : 'Audio generated',
+              // });
+            }
+
+            // Auto-play if enabled and nothing is currently playing
+            if (autoplayRef.current && !isPlayingRef.current) {
+              const genAudioUrl = apiClient.getAudioUrl(id);
+              setAudioWithAutoPlay(genAudioUrl, id, '', '');
+            }
+          } else if (data.status === 'failed' || data.status === 'not_found') {
+            source.close();
+            currentSources.delete(id);
+            removePendingGeneration(id);
+            removePendingStoryAdd(id);
+
+            queryClient.invalidateQueries({ queryKey: ['history'] });
+
+            toast({
+              title: data.status === 'not_found' ? 'Generation not found' : 'Generation failed',
+              description: data.error || 'An error occurred during generation',
+              variant: 'destructive',
+            });
+          }
+        } catch {
+          // Ignore parse errors from heartbeats etc
+        }
+      };
+
+      source.onerror = () => {
+        // EventSource auto-reconnects, but if we get repeated errors
+        // just clean up
+        source.close();
+        currentSources.delete(id);
+        removePendingGeneration(id);
+      };
+
+      currentSources.set(id, source);
+    }
+  }, [
+    pendingIds,
+    removePendingGeneration,
+    removePendingStoryAdd,
+    queryClient,
+    toast,
+    setAudioWithAutoPlay,
+  ]);
+}

app/src/lib/hooks/useModelDownloadToast.tsx

@@ -1,14 +1,16 @@
-import { useEffect, useRef } from 'react';
+import { CheckCircle2, Loader2, XCircle } from 'lucide-react';
-import { useToast } from '@/components/ui/use-toast';
+import { useCallback, useEffect, useRef } from 'react';
-import { useServerStore } from '@/stores/serverStore';
 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?: (error: string) => void;
 }
 
 /**
@@ -19,47 +21,64 @@ 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<
+  // biome-ignore lint: Using any for toast update ref to handle complex toast types
-    ((props: {
+  const toastUpdateRef = useRef<any>(null);
-      title?: React.ReactNode;
-      description?: React.ReactNode;
-      duration?: number;
-      variant?: 'default' | 'destructive';
-      open?: boolean;
-    }) => void) | null
-  >(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">
+          <Loader2 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;
 
@@ -82,11 +101,11 @@ export function useModelDownloadToast({
               break;
             case 'error':
               statusIcon = <XCircle className="h-4 w-4 text-destructive" />;
-              statusText = `Error: ${progress.error || 'Unknown error'}`;
+              statusText = 'Download failed. See Problems panel for details.';
               break;
             case 'downloading':
               statusIcon = <Loader2 className="h-4 w-4 animate-spin" />;
-              statusText = progress.filename ? `Downloading ${progress.filename}...` : 'Downloading...';
+              statusText = progress.filename || 'Downloading...';
               break;
             case 'extracting':
               statusIcon = <Loader2 className="h-4 w-4 animate-spin" />;
@@ -112,26 +131,44 @@ export function useModelDownloadToast({
                 )}
               </div>
             ),
-            duration: progress.status === 'complete' ? 5000 : Infinity,
+            duration: progress.status === 'complete' || progress.status === 'error' ? 5000 : Infinity,
-            variant: progress.status === 'error' ? 'destructive' : 'default',
           });
 
           // 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
+            // Update toast to show completion state before callbacks
-            if (progress.status === 'complete') {
+            if (isComplete && toastUpdateRef.current) {
-              setTimeout(() => {
+              toastUpdateRef.current({
-                if (toastIdRef.current && toastUpdateRef.current) {
+                title: (
-                  toastUpdateRef.current({
+                  <div className="flex items-center gap-2">
-                    open: false,
+                    <CheckCircle2 className="h-4 w-4 text-green-500" />
-                  });
+                    <span>{displayName}</span>
-                  toastIdRef.current = null;
+                  </div>
-                  toastUpdateRef.current = null;
+                ),
-                }
+                description: 'Download complete',
-              }, 5000);
+                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(progress.error || 'Unknown error');
             }
           }
         }
@@ -141,7 +178,8 @@ 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 +200,16 @@ 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,
   };
-}
+}

app/src/lib/hooks/useRestoreActiveTasks.tsx

@@ -1,23 +1,23 @@
 import { useCallback, useEffect, useRef, useState } from 'react';
 import { apiClient } from '@/lib/api/client';
-import { useGenerationStore } from '@/stores/generationStore';
 import type { ActiveDownloadTask } from '@/lib/api/types';
+import { useGenerationStore } from '@/stores/generationStore';
 
 // Polling interval in milliseconds
-const POLL_INTERVAL = 2000;
+const POLL_INTERVAL = 30000;
 
 /**
  * Hook to monitor active tasks (downloads and generations).
  * Polls the server periodically to catch downloads triggered from anywhere
  * (transcription, generation, explicit download, etc.).
- * 
+ *
  * Returns the active downloads so components can render download toasts.
  */
 export function useRestoreActiveTasks() {
   const [activeDownloads, setActiveDownloads] = useState<ActiveDownloadTask[]>([]);
-  const setIsGenerating = useGenerationStore((state) => state.setIsGenerating);
   const setActiveGenerationId = useGenerationStore((state) => state.setActiveGenerationId);
-  
+  const addPendingGeneration = useGenerationStore((state) => state.addPendingGeneration);
+
   // Track which downloads we've seen to detect new ones
   const seenDownloadsRef = useRef<Set<string>>(new Set());
 
@@ -25,15 +25,15 @@ export function useRestoreActiveTasks() {
     try {
       const tasks = await apiClient.getActiveTasks();
 
-      // Update generation state
+      // Restore pending generations (e.g., after page refresh)
       if (tasks.generations.length > 0) {
-        setIsGenerating(true);
         setActiveGenerationId(tasks.generations[0].task_id);
+        for (const gen of tasks.generations) {
+          addPendingGeneration(gen.task_id);
+        }
       } else {
-        // Only clear if we were tracking a generation
         const currentId = useGenerationStore.getState().activeGenerationId;
         if (currentId) {
-          setIsGenerating(false);
           setActiveGenerationId(null);
         }
       }
@@ -41,14 +41,14 @@ export function useRestoreActiveTasks() {
       // Update active downloads
       // Keep track of all active downloads (including new ones)
       const currentDownloadNames = new Set(tasks.downloads.map((d) => d.model_name));
-      
+
       // Remove completed downloads from our seen set
       for (const name of seenDownloadsRef.current) {
         if (!currentDownloadNames.has(name)) {
           seenDownloadsRef.current.delete(name);
         }
       }
-      
+
       // Add new downloads to seen set
       for (const download of tasks.downloads) {
         seenDownloadsRef.current.add(download.model_name);
@@ -59,7 +59,7 @@ export function useRestoreActiveTasks() {
       // Silently fail - server might be temporarily unavailable
       console.debug('Failed to fetch active tasks:', error);
     }
-  }, [setIsGenerating, setActiveGenerationId]);
+  }, [setActiveGenerationId, addPendingGeneration]);
 
   useEffect(() => {
     // Fetch immediately on mount

app/src/lib/utils/audio.ts

@@ -22,6 +22,11 @@ export function formatAudioDuration(seconds: number): string {
  * If the file has a recordedDuration property (from recording hooks),
  * use that instead of trying to read metadata. This fixes issues on Windows
  * where WebM files from MediaRecorder don't have proper duration metadata.
+ *
+ * For uploaded files we use AudioContext.decodeAudioData which fully decodes
+ * the audio and returns the exact duration. This is more reliable than
+ * HTMLMediaElement.duration which can return incorrect large values for VBR
+ * MP3 files that lack a proper XING/VBRI header.
  */
 export async function getAudioDuration(
   file: File & { recordedDuration?: number },
@@ -30,26 +35,39 @@ export async function getAudioDuration(
     return file.recordedDuration;
   }
 
-  return new Promise((resolve, reject) => {
+  // Use Web Audio API for accurate duration — avoids VBR MP3 metadata issues.
-    const audio = new Audio();
+  try {
-    const url = URL.createObjectURL(file);
+    const audioContext = new AudioContext();
+    try {
+      const arrayBuffer = await file.arrayBuffer();
+      const audioBuffer = await audioContext.decodeAudioData(arrayBuffer);
+      return audioBuffer.duration;
+    } finally {
+      await audioContext.close();
+    }
+  } catch {
+    // Fallback: read duration from the media element (less accurate but works for WAV).
+    return new Promise((resolve, reject) => {
+      const audio = new Audio();
+      const url = URL.createObjectURL(file);
 
-    audio.addEventListener('loadedmetadata', () => {
+      audio.addEventListener('loadedmetadata', () => {
-      URL.revokeObjectURL(url);
+        URL.revokeObjectURL(url);
-      if (Number.isFinite(audio.duration) && audio.duration > 0) {
+        if (Number.isFinite(audio.duration) && audio.duration > 0) {
-        resolve(audio.duration);
+          resolve(audio.duration);
-      } else {
+        } else {
-        reject(new Error('Audio file has invalid duration metadata'));
+          reject(new Error('Audio file has invalid duration metadata'));
-      }
+        }
+      });
+
+      audio.addEventListener('error', () => {
+        URL.revokeObjectURL(url);
+        reject(new Error('Failed to load audio file'));
+      });
+
+      audio.src = url;
     });
-
+  }
-    audio.addEventListener('error', () => {
-      URL.revokeObjectURL(url);
-      reject(new Error('Failed to load audio file'));
-    });
-
-    audio.src = url;
-  });
 }
 
 /**

app/src/lib/utils/format.ts

@@ -21,10 +21,25 @@ export function formatDate(date: string | Date): string {
   } else {
     dateObj = date;
   }
-  
+
   return formatDistance(dateObj, new Date(), { addSuffix: true }).replace(/^about /i, '');
 }
 
+const ENGINE_DISPLAY_NAMES: Record<string, string> = {
+  qwen: 'Qwen',
+  luxtts: 'LuxTTS',
+  chatterbox: 'Chatterbox',
+  chatterbox_turbo: 'Chatterbox Turbo',
+};
+
+export function formatEngineName(engine?: string, modelSize?: string): string {
+  const name = ENGINE_DISPLAY_NAMES[engine ?? 'qwen'] ?? engine ?? 'Qwen';
+  if (engine === 'qwen' && modelSize) {
+    return `${name} ${modelSize}`;
+  }
+  return name;
+}
+
 export function formatFileSize(bytes: number): string {
   if (bytes === 0) return '0 Bytes';
   const k = 1024;

app/src/platform/types.ts

@@ -49,8 +49,9 @@ export interface PlatformAudio {
 }
 
 export interface PlatformLifecycle {
-  startServer(remote?: boolean): Promise<string>;
+  startServer(remote?: boolean, modelsDir?: string | null): Promise<string>;
   stopServer(): Promise<void>;
+  restartServer(modelsDir?: string | null): Promise<string>;
   setKeepServerRunning(keep: boolean): Promise<void>;
   setupWindowCloseHandler(): Promise<void>;
   onServerReady?: () => void;

app/src/router.tsx

@@ -8,8 +8,10 @@ import { Sidebar } from '@/components/Sidebar';
 import { StoriesTab } from '@/components/StoriesTab/StoriesTab';
 import { Toaster } from '@/components/ui/toaster';
 import { VoicesTab } from '@/components/VoicesTab/VoicesTab';
+import { useGenerationProgress } from '@/lib/hooks/useGenerationProgress';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
 import { MODEL_DISPLAY_NAMES, useRestoreActiveTasks } from '@/lib/hooks/useRestoreActiveTasks';
+
 // Simple platform check that works in both web and Tauri
 const isMacOS = () => navigator.platform.toLowerCase().includes('mac');
 
@@ -18,6 +20,9 @@ function RootLayout() {
   // Monitor active downloads/generations and show toasts for them
   const activeDownloads = useRestoreActiveTasks();
 
+  // Subscribe to SSE for pending generations — handles completion, auto-play, and history refresh
+  useGenerationProgress();
+
   return (
     <AppFrame>
       <div className="flex flex-1 min-h-0 overflow-hidden">

app/src/stores/generationStore.ts

@@ -1,15 +1,58 @@
 import { create } from 'zustand';
 
 interface GenerationState {
+  /** IDs of generations currently in progress */
+  pendingGenerationIds: Set<string>;
+  /** Whether any generation is in progress (derived from pendingGenerationIds) */
   isGenerating: boolean;
-  activeGenerationId: string | null;
+  /** Map of generationId → storyId for deferred story additions */
-  setIsGenerating: (generating: boolean) => void;
+  pendingStoryAdds: Map<string, string>;
+  addPendingGeneration: (id: string) => void;
+  removePendingGeneration: (id: string) => void;
+  addPendingStoryAdd: (generationId: string, storyId: string) => void;
+  removePendingStoryAdd: (generationId: string) => string | undefined;
   setActiveGenerationId: (id: string | null) => void;
+  activeGenerationId: string | null;
 }
 
-export const useGenerationStore = create<GenerationState>((set) => ({
+export const useGenerationStore = create<GenerationState>((set, get) => ({
+  pendingGenerationIds: new Set(),
   isGenerating: false,
   activeGenerationId: null,
-  setIsGenerating: (generating) => set({ isGenerating: generating }),
+  pendingStoryAdds: new Map(),
+
+  addPendingGeneration: (id) =>
+    set((state) => {
+      const next = new Set(state.pendingGenerationIds);
+      next.add(id);
+      return { pendingGenerationIds: next, isGenerating: true };
+    }),
+
+  removePendingGeneration: (id) =>
+    set((state) => {
+      const next = new Set(state.pendingGenerationIds);
+      next.delete(id);
+      return { pendingGenerationIds: next, isGenerating: next.size > 0 };
+    }),
+
+  addPendingStoryAdd: (generationId, storyId) =>
+    set((state) => {
+      const next = new Map(state.pendingStoryAdds);
+      next.set(generationId, storyId);
+      return { pendingStoryAdds: next };
+    }),
+
+  removePendingStoryAdd: (generationId) => {
+    const storyId = get().pendingStoryAdds.get(generationId);
+    if (storyId) {
+      set((state) => {
+        const next = new Map(state.pendingStoryAdds);
+        next.delete(generationId);
+        return { pendingStoryAdds: next };
+      });
+    }
+    return storyId;
+  },
+
   setActiveGenerationId: (id) => set({ activeGenerationId: id }),
 }));

app/src/stores/serverStore.ts

@@ -13,6 +13,21 @@ interface ServerStore {
 
   keepServerRunningOnClose: boolean;
   setKeepServerRunningOnClose: (keepRunning: boolean) => void;
+
+  maxChunkChars: number;
+  setMaxChunkChars: (value: number) => void;
+
+  crossfadeMs: number;
+  setCrossfadeMs: (value: number) => void;
+
+  normalizeAudio: boolean;
+  setNormalizeAudio: (value: boolean) => void;
+
+  autoplayOnGenerate: boolean;
+  setAutoplayOnGenerate: (value: boolean) => void;
+
+  customModelsDir: string | null;
+  setCustomModelsDir: (dir: string | null) => void;
 }
 
 export const useServerStore = create<ServerStore>()(
@@ -29,6 +44,21 @@ export const useServerStore = create<ServerStore>()(
 
       keepServerRunningOnClose: false,
       setKeepServerRunningOnClose: (keepRunning) => set({ keepServerRunningOnClose: keepRunning }),
+
+      maxChunkChars: 800,
+      setMaxChunkChars: (value) => set({ maxChunkChars: value }),
+
+      crossfadeMs: 50,
+      setCrossfadeMs: (value) => set({ crossfadeMs: value }),
+
+      normalizeAudio: true,
+      setNormalizeAudio: (value) => set({ normalizeAudio: value }),
+
+      autoplayOnGenerate: true,
+      setAutoplayOnGenerate: (value) => set({ autoplayOnGenerate: value }),
+
+      customModelsDir: null,
+      setCustomModelsDir: (dir) => set({ customModelsDir: dir }),
     }),
     {
       name: 'voicebox-server',

backend/README.md

@@ -334,18 +334,21 @@ python -m backend.main --host 0.0.0.0 --port 8000
 
 ## Usage Examples
 
+The desktop app, web client, and current development workflow use `http://localhost:17493` by default.
+If you launch the backend manually with a different host or port, substitute that address in the examples below.
+
 ### Creating a Voice Profile
 
 ```bash
 # 1. Create profile
-curl -X POST http://localhost:8000/profiles \
+curl -X POST http://localhost:17493/profiles \
   -H "Content-Type: application/json" \
   -d '{"name": "My Voice", "language": "en"}'
 
 # Response: {"id": "abc-123", ...}
 
 # 2. Add sample
-curl -X POST http://localhost:8000/profiles/abc-123/samples \
+curl -X POST http://localhost:17493/profiles/abc-123/samples \
   -F "file=@sample.wav" \
   -F "reference_text=This is my voice sample"
 ```
@@ -353,7 +356,7 @@ curl -X POST http://localhost:8000/profiles/abc-123/samples \
 ### Generating Speech
 
 ```bash
-curl -X POST http://localhost:8000/generate \
+curl -X POST http://localhost:17493/generate \
   -H "Content-Type: application/json" \
   -d '{
     "profile_id": "abc-123",
@@ -365,13 +368,13 @@ curl -X POST http://localhost:8000/generate \
 # Response: {"id": "gen-456", "audio_path": "/path/to/audio.wav", ...}
 
 # Download audio
-curl http://localhost:8000/audio/gen-456 -o output.wav
+curl http://localhost:17493/audio/gen-456 -o output.wav
 ```
 
 ### Transcribing Audio
 
 ```bash
-curl -X POST http://localhost:8000/transcribe \
+curl -X POST http://localhost:17493/transcribe \
   -F "file=@audio.wav" \
   -F "language=en"
 
@@ -386,12 +389,12 @@ Add multiple samples to a profile for better quality:
 
 ```bash
 # Add first sample
-curl -X POST http://localhost:8000/profiles/abc-123/samples \
+curl -X POST http://localhost:17493/profiles/abc-123/samples \
   -F "file=@sample1.wav" \
   -F "reference_text=First sample"
 
 # Add second sample
-curl -X POST http://localhost:8000/profiles/abc-123/samples \
+curl -X POST http://localhost:17493/profiles/abc-123/samples \
   -F "file=@sample2.wav" \
   -F "reference_text=Second sample"
 
@@ -412,10 +415,10 @@ Models are lazy-loaded and can be manually unloaded:
 
 ```bash
 # Unload TTS model
-curl -X POST http://localhost:8000/models/unload
+curl -X POST http://localhost:17493/models/unload
 
 # Load specific model size
-curl -X POST "http://localhost:8000/models/load?model_size=0.6B"
+curl -X POST "http://localhost:17493/models/load?model_size=0.6B"
 ```
 
 ## Error Handling

backend/__init__.py

@@ -1,3 +1,3 @@
 # Backend package
 
-__version__ = "0.1.11"
+__version__ = "0.1.13"

backend/backends/__init__.py

@@ -4,6 +4,7 @@ Backend abstraction layer for TTS and STT.
 Provides a unified interface for MLX and PyTorch backends.
 """
 
+import threading
 from typing import Protocol, Optional, Tuple, List
 from typing_extensions import runtime_checkable
 import numpy as np
@@ -112,29 +113,73 @@ class STTBackend(Protocol):
 
 # Global backend instances
 _tts_backend: Optional[TTSBackend] = None
+_tts_backends: dict[str, TTSBackend] = {}
+_tts_backends_lock = threading.Lock()
 _stt_backend: Optional[STTBackend] = None
 
+# Supported TTS engines
+TTS_ENGINES = {
+    "qwen": "Qwen TTS",
+    "luxtts": "LuxTTS",
+    "chatterbox": "Chatterbox TTS",
+    "chatterbox_turbo": "Chatterbox Turbo",
+}
+
 
 def get_tts_backend() -> TTSBackend:
     """
-    Get or create TTS backend instance based on platform.
+    Get or create the default (Qwen) TTS backend instance based on platform.
     
     Returns:
         TTS backend instance (MLX or PyTorch)
     """
-    global _tts_backend
+    return get_tts_backend_for_engine("qwen")
+
+
+def get_tts_backend_for_engine(engine: str) -> TTSBackend:
+    """
+    Get or create a TTS backend for the given engine.
     
-    if _tts_backend is None:
+    Args:
-        backend_type = get_backend_type()
+        engine: Engine name ("qwen" or "luxtts")
+    
+    Returns:
+        TTS backend instance
+    """
+    global _tts_backends
+    
+    # Fast path: check without lock
+    if engine in _tts_backends:
+        return _tts_backends[engine]
+    
+    # Slow path: create with lock to avoid duplicate instantiation
+    with _tts_backends_lock:
+        # Double-check after acquiring lock
+        if engine in _tts_backends:
+            return _tts_backends[engine]
         
-        if backend_type == "mlx":
+        if engine == "qwen":
-            from .mlx_backend import MLXTTSBackend
+            backend_type = get_backend_type()
-            _tts_backend = MLXTTSBackend()
+            if backend_type == "mlx":
+                from .mlx_backend import MLXTTSBackend
+                backend = MLXTTSBackend()
+            else:
+                from .pytorch_backend import PyTorchTTSBackend
+                backend = PyTorchTTSBackend()
+        elif engine == "luxtts":
+            from .luxtts_backend import LuxTTSBackend
+            backend = LuxTTSBackend()
+        elif engine == "chatterbox":
+            from .chatterbox_backend import ChatterboxTTSBackend
+            backend = ChatterboxTTSBackend()
+        elif engine == "chatterbox_turbo":
+            from .chatterbox_turbo_backend import ChatterboxTurboTTSBackend
+            backend = ChatterboxTurboTTSBackend()
         else:
-            from .pytorch_backend import PyTorchTTSBackend
+            raise ValueError(f"Unknown TTS engine: {engine}. Supported: {list(TTS_ENGINES.keys())}")
-            _tts_backend = PyTorchTTSBackend()
+        
-    
+        _tts_backends[engine] = backend
-    return _tts_backend
+        return backend
 
 
 def get_stt_backend() -> STTBackend:
@@ -161,6 +206,7 @@ def get_stt_backend() -> STTBackend:
 
 def reset_backends():
     """Reset backend instances (useful for testing)."""
-    global _tts_backend, _stt_backend
+    global _tts_backend, _tts_backends, _stt_backend
     _tts_backend = None
+    _tts_backends.clear()
     _stt_backend = None

backend/backends/chatterbox_backend.py

@@ -0,0 +1,360 @@
+"""
+Chatterbox TTS backend implementation.
+
+Wraps ChatterboxMultilingualTTS from chatterbox-tts for zero-shot
+voice cloning. Supports 23 languages including Hebrew. Forces CPU
+on macOS due to known MPS tensor issues.
+"""
+
+import asyncio
+import logging
+import platform
+import threading
+from pathlib import Path
+from typing import ClassVar, List, Optional, Tuple
+
+import numpy as np
+
+from . import TTSBackend
+from ..utils.audio import normalize_audio, load_audio
+from ..utils.progress import get_progress_manager
+from ..utils.tasks import get_task_manager
+
+logger = logging.getLogger(__name__)
+
+CHATTERBOX_HF_REPO = "ResembleAI/chatterbox"
+
+# Files that must be present for the multilingual model
+_MTL_WEIGHT_FILES = [
+    "t3_mtl23ls_v2.safetensors",
+    "s3gen.pt",
+    "ve.pt",
+]
+
+
+class ChatterboxTTSBackend:
+    """Chatterbox Multilingual TTS backend for voice cloning."""
+
+    # Class-level lock for torch.load monkey-patching
+    _load_lock: ClassVar[threading.Lock] = threading.Lock()
+
+    def __init__(self):
+        self.model = None
+        self.model_size = "default"
+        self._device = None
+        self._model_load_lock = asyncio.Lock()
+
+    def _get_device(self) -> str:
+        """Get the best available device. Forces CPU on macOS (MPS issue)."""
+        if platform.system() == "Darwin":
+            return "cpu"
+        try:
+            import torch
+
+            if torch.cuda.is_available():
+                return "cuda"
+        except ImportError:
+            pass
+        return "cpu"
+
+    def is_loaded(self) -> bool:
+        return self.model is not None
+
+    def _get_model_path(self, model_size: str = "default") -> str:
+        return CHATTERBOX_HF_REPO
+
+    def _is_model_cached(self, model_size: str = "default") -> bool:
+        """Check if the Chatterbox multilingual model is cached locally."""
+        try:
+            from huggingface_hub import constants as hf_constants
+
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / (
+                "models--" + CHATTERBOX_HF_REPO.replace("/", "--")
+            )
+
+            if not repo_cache.exists():
+                return False
+
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                return False
+
+            # Check for multilingual weight files
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                for fname in _MTL_WEIGHT_FILES:
+                    if not any(snapshots_dir.rglob(fname)):
+                        return False
+                return True
+
+            return False
+        except Exception as e:
+            logger.warning(f"Error checking Chatterbox cache: {e}")
+            return False
+
+    async def load_model(self, model_size: str = "default") -> None:
+        """Load the Chatterbox multilingual model."""
+        if self.model is not None:
+            return
+        async with self._model_load_lock:
+            if self.model is not None:
+                return
+            await asyncio.to_thread(self._load_model_sync)
+
+    def _load_model_sync(self):
+        """Synchronous model loading."""
+        from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+
+        progress_manager = get_progress_manager()
+        task_manager = get_task_manager()
+        model_name = "chatterbox-tts"
+
+        is_cached = self._is_model_cached()
+
+        # Set up HF progress tracking (intercepts tqdm for file-level progress)
+        progress_callback = create_hf_progress_callback(model_name, progress_manager)
+        tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+        tracker_context = tracker.patch_download()
+        tracker_context.__enter__()
+
+        if not is_cached:
+            task_manager.start_download(model_name)
+            progress_manager.update_progress(
+                model_name=model_name,
+                current=0,
+                total=0,
+                filename="Connecting to HuggingFace...",
+                status="downloading",
+            )
+
+        try:
+            device = self._get_device()
+            self._device = device
+
+            logger.info(f"Loading Chatterbox Multilingual TTS on {device}...")
+
+            import torch
+            from chatterbox.mtl_tts import ChatterboxMultilingualTTS
+
+            # Load into a local variable first, apply all patches, then
+            # assign to self.model.  This avoids leaving a half-initialised
+            # model on self.model if any patch step raises an exception.
+            #
+            # Monkey-patch torch.load for CPU loading. The model's .pt files
+            # were saved on CUDA; from_pretrained() doesn't pass map_location
+            # so loading on CPU fails without this.
+            try:
+                if device == "cpu":
+                    _orig_torch_load = torch.load
+
+                    def _patched_load(*args, **kwargs):
+                        kwargs.setdefault("map_location", "cpu")
+                        return _orig_torch_load(*args, **kwargs)
+
+                    with ChatterboxTTSBackend._load_lock:
+                        torch.load = _patched_load
+                        try:
+                            model = ChatterboxMultilingualTTS.from_pretrained(
+                                device=device,
+                            )
+                        finally:
+                            torch.load = _orig_torch_load
+                else:
+                    model = ChatterboxMultilingualTTS.from_pretrained(
+                        device=device,
+                    )
+            finally:
+                tracker_context.__exit__(None, None, None)
+
+            # Fix: transformers >= 4.36 defaults LlamaModel to sdpa attention
+            # which doesn't support output_attentions=True (needed by
+            # Chatterbox's AlignmentStreamAnalyzer). Force eager attention.
+            t3_tfmr = model.t3.tfmr
+            if hasattr(t3_tfmr, "config") and hasattr(
+                t3_tfmr.config, "_attn_implementation"
+            ):
+                t3_tfmr.config._attn_implementation = "eager"
+                for layer in getattr(t3_tfmr, "layers", []):
+                    if hasattr(layer, "self_attn"):
+                        layer.self_attn._attn_implementation = "eager"
+
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+
+            # Patch float64 → float32 dtype mismatches in upstream chatterbox.
+            # librosa.load returns float64 numpy; multiple upstream code paths
+            # convert it to a torch tensor via torch.from_numpy() without
+            # casting, then matmul it against float32 model weights.
+            import types
+
+            # Patch S3Tokenizer (used by s3gen.tokenizer)
+            _tokzr = model.s3gen.tokenizer
+            _orig_log_mel = _tokzr.log_mel_spectrogram.__func__
+
+            def _f32_log_mel(self_tokzr, audio, padding=0):
+                import torch as _torch
+                if _torch.is_tensor(audio):
+                    audio = audio.float()
+                return _orig_log_mel(self_tokzr, audio, padding)
+
+            _tokzr.log_mel_spectrogram = types.MethodType(_f32_log_mel, _tokzr)
+
+            # Patch VoiceEncoder
+            _ve = model.ve
+            _orig_ve_forward = _ve.forward.__func__
+
+            def _f32_ve_forward(self_ve, mels):
+                return _orig_ve_forward(self_ve, mels.float())
+
+            _ve.forward = types.MethodType(_f32_ve_forward, _ve)
+
+            # All patches applied successfully — publish the model
+            self.model = model
+
+            logger.info("Chatterbox Multilingual TTS loaded successfully")
+
+        except ImportError as e:
+            logger.error(
+                "chatterbox-tts package not found. "
+                "Install with: pip install chatterbox-tts"
+            )
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+        except Exception as e:
+            logger.error(f"Failed to load Chatterbox: {e}")
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        if self.model is not None:
+            device = self._device
+            del self.model
+            self.model = None
+            self._device = None
+            if device == "cuda":
+                import torch
+
+                torch.cuda.empty_cache()
+            logger.info("Chatterbox unloaded")
+
+    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.
+
+        Chatterbox processes reference audio at generation time, so the
+        prompt just stores the file path. The actual audio is loaded by
+        model.generate() via audio_prompt_path.
+        """
+        voice_prompt = {
+            "ref_audio": str(audio_path),
+            "ref_text": reference_text,
+        }
+        return voice_prompt, False
+
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """Combine multiple reference samples."""
+        combined_audio = []
+        for path in audio_paths:
+            audio, _sr = load_audio(path)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        combined_text = " ".join(reference_texts)
+        return mixed, combined_text
+
+    # Per-language generation defaults. Lower temp + higher cfg = clearer speech.
+    _LANG_DEFAULTS: ClassVar[dict] = {
+        "he": {
+            "exaggeration": 0.4,
+            "cfg_weight": 0.7,
+            "temperature": 0.65,
+            "repetition_penalty": 2.5,
+        },
+    }
+    _GLOBAL_DEFAULTS: ClassVar[dict] = {
+        "exaggeration": 0.5,
+        "cfg_weight": 0.5,
+        "temperature": 0.8,
+        "repetition_penalty": 2.0,
+    }
+
+    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 audio using Chatterbox Multilingual TTS.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Dict with ref_audio path
+            language: BCP-47 language code
+            seed: Random seed for reproducibility
+            instruct: Unused (protocol compatibility)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model()
+
+        ref_audio = voice_prompt.get("ref_audio")
+        if ref_audio and not Path(ref_audio).exists():
+            logger.warning(f"Reference audio not found: {ref_audio}")
+            ref_audio = None
+
+        # Merge language-specific defaults with global defaults
+        lang_defaults = self._LANG_DEFAULTS.get(language, self._GLOBAL_DEFAULTS)
+
+        def _generate_sync():
+            import torch
+
+            if seed is not None:
+                torch.manual_seed(seed)
+
+            logger.info(f"[Chatterbox] Generating: lang={language}")
+
+            wav = self.model.generate(
+                text,
+                language_id=language,
+                audio_prompt_path=ref_audio,
+                exaggeration=lang_defaults["exaggeration"],
+                cfg_weight=lang_defaults["cfg_weight"],
+                temperature=lang_defaults["temperature"],
+                repetition_penalty=lang_defaults["repetition_penalty"],
+            )
+
+            # Convert tensor -> numpy
+            if isinstance(wav, torch.Tensor):
+                audio = wav.squeeze().cpu().numpy().astype(np.float32)
+            else:
+                audio = np.asarray(wav, dtype=np.float32)
+
+            sample_rate = (
+                getattr(self.model, "sr", None)
+                or getattr(self.model, "sample_rate", 24000)
+            )
+
+            return audio, sample_rate
+
+        return await asyncio.to_thread(_generate_sync)

backend/backends/chatterbox_turbo_backend.py

@@ -0,0 +1,345 @@
+"""
+Chatterbox Turbo TTS backend implementation.
+
+Wraps ChatterboxTurboTTS from chatterbox-tts for fast, English-only
+voice cloning with paralinguistic tag support ([laugh], [cough], etc.).
+Forces CPU on macOS due to known MPS tensor issues.
+"""
+
+import asyncio
+import logging
+import platform
+import threading
+from pathlib import Path
+from typing import ClassVar, List, Optional, Tuple
+
+import numpy as np
+
+from . import TTSBackend
+from ..utils.audio import normalize_audio, load_audio
+from ..utils.progress import get_progress_manager
+from ..utils.tasks import get_task_manager
+
+logger = logging.getLogger(__name__)
+
+CHATTERBOX_TURBO_HF_REPO = "ResembleAI/chatterbox-turbo"
+
+# Files that must be present for the turbo model
+_TURBO_WEIGHT_FILES = [
+    "t3_turbo_v1.safetensors",
+    "s3gen_meanflow.safetensors",
+    "ve.safetensors",
+]
+
+
+class ChatterboxTurboTTSBackend:
+    """Chatterbox Turbo TTS backend — fast, English-only, with paralinguistic tags."""
+
+    # Class-level lock for torch.load monkey-patching
+    _load_lock: ClassVar[threading.Lock] = threading.Lock()
+
+    def __init__(self):
+        self.model = None
+        self.model_size = "default"
+        self._device = None
+        self._model_load_lock = asyncio.Lock()
+
+    def _get_device(self) -> str:
+        """Get the best available device. Forces CPU on macOS (MPS issue)."""
+        if platform.system() == "Darwin":
+            return "cpu"
+        try:
+            import torch
+
+            if torch.cuda.is_available():
+                return "cuda"
+        except ImportError:
+            pass
+        return "cpu"
+
+    def is_loaded(self) -> bool:
+        return self.model is not None
+
+    def _get_model_path(self, model_size: str = "default") -> str:
+        return CHATTERBOX_TURBO_HF_REPO
+
+    def _is_model_cached(self, model_size: str = "default") -> bool:
+        """Check if the Chatterbox Turbo model is cached locally."""
+        try:
+            from huggingface_hub import constants as hf_constants
+
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / (
+                "models--" + CHATTERBOX_TURBO_HF_REPO.replace("/", "--")
+            )
+
+            if not repo_cache.exists():
+                return False
+
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                return False
+
+            # Check for turbo weight files
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                for fname in _TURBO_WEIGHT_FILES:
+                    if not any(snapshots_dir.rglob(fname)):
+                        return False
+                return True
+
+            return False
+        except Exception as e:
+            logger.warning(f"Error checking Chatterbox Turbo cache: {e}")
+            return False
+
+    async def load_model(self, model_size: str = "default") -> None:
+        """Load the Chatterbox Turbo model."""
+        if self.model is not None:
+            return
+        async with self._model_load_lock:
+            if self.model is not None:
+                return
+            await asyncio.to_thread(self._load_model_sync)
+
+    def _load_model_sync(self):
+        """Synchronous model loading."""
+        from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+
+        progress_manager = get_progress_manager()
+        task_manager = get_task_manager()
+        model_name = "chatterbox-turbo"
+
+        is_cached = self._is_model_cached()
+
+        # Set up HF progress tracking (intercepts tqdm for file-level progress)
+        progress_callback = create_hf_progress_callback(model_name, progress_manager)
+        tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+        tracker_context = tracker.patch_download()
+        tracker_context.__enter__()
+
+        if not is_cached:
+            task_manager.start_download(model_name)
+            progress_manager.update_progress(
+                model_name=model_name,
+                current=0,
+                total=0,
+                filename="Connecting to HuggingFace...",
+                status="downloading",
+            )
+
+        try:
+            device = self._get_device()
+            self._device = device
+
+            logger.info(f"Loading Chatterbox Turbo TTS on {device}...")
+
+            import torch
+            from huggingface_hub import snapshot_download
+            from chatterbox.tts_turbo import ChatterboxTurboTTS
+
+            # Download model files ourselves so we can pass token=None
+            # (upstream from_pretrained passes token=True which requires
+            # a stored HF token even though the repo is public).
+            try:
+                local_path = snapshot_download(
+                    repo_id=CHATTERBOX_TURBO_HF_REPO,
+                    token=None,
+                    allow_patterns=[
+                        "*.safetensors", "*.json", "*.txt", "*.pt", "*.model",
+                    ],
+                )
+            finally:
+                tracker_context.__exit__(None, None, None)
+
+            # Monkey-patch torch.load for CPU loading. The model's .pt files
+            # were saved on CUDA; from_local() doesn't pass map_location
+            # so loading on CPU fails without this.
+            # Load into a local var, apply patches, then publish to
+            # self.model so a failed patch doesn't leave us half-initialised.
+            if device == "cpu":
+                _orig_torch_load = torch.load
+
+                def _patched_load(*args, **kwargs):
+                    kwargs.setdefault("map_location", "cpu")
+                    return _orig_torch_load(*args, **kwargs)
+
+                with ChatterboxTurboTTSBackend._load_lock:
+                    torch.load = _patched_load
+                    try:
+                        model = ChatterboxTurboTTS.from_local(
+                            local_path, device,
+                        )
+                    finally:
+                        torch.load = _orig_torch_load
+            else:
+                model = ChatterboxTurboTTS.from_local(
+                    local_path, device,
+                )
+
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+
+            # Patch float64 → float32 dtype mismatches in upstream chatterbox.
+            # librosa.load returns float64 numpy; multiple upstream code paths
+            # convert it to a torch tensor via torch.from_numpy() without
+            # casting, then matmul it against float32 model weights.
+            # We patch the two known entry points:
+            #
+            # 1. S3Tokenizer.log_mel_spectrogram — the audio tensor from
+            #    librosa hits _mel_filters (float32) in a matmul.
+            # 2. VoiceEncoder.forward — float64 mel spectrograms hit the
+            #    float32 LSTM weights.
+            import types
+
+            # Patch S3Tokenizer (used by s3gen.tokenizer)
+            _tokzr = model.s3gen.tokenizer
+            _orig_log_mel = _tokzr.log_mel_spectrogram.__func__
+
+            def _f32_log_mel(self_tokzr, audio, padding=0):
+                import torch as _torch
+                if _torch.is_tensor(audio):
+                    audio = audio.float()
+                return _orig_log_mel(self_tokzr, audio, padding)
+
+            _tokzr.log_mel_spectrogram = types.MethodType(_f32_log_mel, _tokzr)
+
+            # Patch VoiceEncoder
+            _ve = model.ve
+            _orig_ve_forward = _ve.forward.__func__
+
+            def _f32_ve_forward(self_ve, mels):
+                return _orig_ve_forward(self_ve, mels.float())
+
+            _ve.forward = types.MethodType(_f32_ve_forward, _ve)
+
+            # Only publish after all patches succeed
+            self.model = model
+
+            logger.info("Chatterbox Turbo TTS loaded successfully")
+
+        except ImportError as e:
+            logger.error(
+                "chatterbox-tts package not found. "
+                "Install with: pip install chatterbox-tts"
+            )
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+        except Exception as e:
+            logger.error(f"Failed to load Chatterbox Turbo: {e}")
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        if self.model is not None:
+            device = self._device
+            del self.model
+            self.model = None
+            self._device = None
+            if device == "cuda":
+                import torch
+
+                torch.cuda.empty_cache()
+            logger.info("Chatterbox Turbo unloaded")
+
+    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.
+
+        Chatterbox Turbo processes reference audio at generation time, so the
+        prompt just stores the file path.
+        """
+        voice_prompt = {
+            "ref_audio": str(audio_path),
+            "ref_text": reference_text,
+        }
+        return voice_prompt, False
+
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """Combine multiple reference samples."""
+        combined_audio = []
+        for path in audio_paths:
+            audio, _sr = load_audio(path)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        combined_text = " ".join(reference_texts)
+        return mixed, combined_text
+
+    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 audio using Chatterbox Turbo TTS.
+
+        Supports paralinguistic tags in text: [laugh], [cough], [chuckle], etc.
+
+        Args:
+            text: Text to synthesize (may include paralinguistic tags)
+            voice_prompt: Dict with ref_audio path
+            language: Ignored (Turbo is English-only)
+            seed: Random seed for reproducibility
+            instruct: Unused (protocol compatibility)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model()
+
+        ref_audio = voice_prompt.get("ref_audio")
+        if ref_audio and not Path(ref_audio).exists():
+            logger.warning(f"Reference audio not found: {ref_audio}")
+            ref_audio = None
+
+        def _generate_sync():
+            import torch
+
+            if seed is not None:
+                torch.manual_seed(seed)
+
+            logger.info("[Chatterbox Turbo] Generating (English)")
+
+            wav = self.model.generate(
+                text,
+                audio_prompt_path=ref_audio,
+                temperature=0.8,
+                top_k=1000,
+                top_p=0.95,
+                repetition_penalty=1.2,
+            )
+
+            # Convert tensor -> numpy
+            if isinstance(wav, torch.Tensor):
+                audio = wav.squeeze().cpu().numpy().astype(np.float32)
+            else:
+                audio = np.asarray(wav, dtype=np.float32)
+
+            sample_rate = (
+                getattr(self.model, "sr", None)
+                or getattr(self.model, "sample_rate", 24000)
+            )
+
+            return audio, sample_rate
+
+        return await asyncio.to_thread(_generate_sync)

backend/backends/luxtts_backend.py

@@ -0,0 +1,275 @@
+"""
+LuxTTS backend implementation.
+
+Wraps the LuxTTS (ZipVoice) model for zero-shot voice cloning.
+~1GB VRAM, 48kHz output, 150x realtime on CPU.
+"""
+
+import asyncio
+import logging
+from pathlib import Path
+from typing import List, Optional, Tuple
+
+import numpy as np
+
+from . import TTSBackend
+from ..utils.audio import normalize_audio, load_audio
+from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
+from ..utils.progress import get_progress_manager
+from ..utils.tasks import get_task_manager
+
+logger = logging.getLogger(__name__)
+
+# HuggingFace repo for model weight detection
+LUXTTS_HF_REPO = "YatharthS/LuxTTS"
+
+
+class LuxTTSBackend:
+    """LuxTTS backend for zero-shot voice cloning."""
+
+    def __init__(self):
+        self.model = None
+        self.model_size = "default"  # LuxTTS has only one model size
+        self._device = None
+
+    def _get_device(self) -> str:
+        """Get the best available device."""
+        import torch
+
+        if torch.cuda.is_available():
+            return "cuda"
+        if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+            return "mps"
+        return "cpu"
+
+    def is_loaded(self) -> bool:
+        return self.model is not None
+
+    @property
+    def device(self) -> str:
+        if self._device is None:
+            self._device = self._get_device()
+        return self._device
+
+    def _get_model_path(self, model_size: str) -> str:
+        return LUXTTS_HF_REPO
+
+    def _is_model_cached(self, model_size: str = "default") -> bool:
+        """Check if LuxTTS model weights are cached locally."""
+        try:
+            from huggingface_hub import constants as hf_constants
+
+            repo_cache = (
+                Path(hf_constants.HF_HUB_CACHE)
+                / ("models--" + LUXTTS_HF_REPO.replace("/", "--"))
+            )
+
+            if not repo_cache.exists():
+                return False
+
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                return False
+
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = any(snapshots_dir.rglob("*.pt")) or any(
+                    snapshots_dir.rglob("*.safetensors")
+                ) or any(snapshots_dir.rglob("*.onnx")) or any(
+                    snapshots_dir.rglob("*.bin")
+                )
+                return has_weights
+
+            return False
+        except Exception as e:
+            logger.warning(f"Error checking LuxTTS cache: {e}")
+            return False
+
+    async def load_model(self, model_size: str = "default") -> None:
+        """Load the LuxTTS model."""
+        if self.model is not None:
+            return
+
+        await asyncio.to_thread(self._load_model_sync)
+
+    def _load_model_sync(self):
+        """Synchronous model loading."""
+        from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+
+        progress_manager = get_progress_manager()
+        task_manager = get_task_manager()
+        model_name = "luxtts"
+
+        is_cached = self._is_model_cached()
+
+        # Set up HF progress tracking (intercepts tqdm for file-level progress)
+        progress_callback = create_hf_progress_callback(model_name, progress_manager)
+        tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+        tracker_context = tracker.patch_download()
+        tracker_context.__enter__()
+
+        if not is_cached:
+            task_manager.start_download(model_name)
+            progress_manager.update_progress(
+                model_name=model_name,
+                current=0,
+                total=0,
+                filename="Connecting to HuggingFace...",
+                status="downloading",
+            )
+
+        try:
+            from zipvoice.luxvoice import LuxTTS
+
+            device = self.device
+            logger.info(f"Loading LuxTTS on {device}...")
+
+            # LuxTTS constructor downloads model and loads everything
+            try:
+                if device == "cpu":
+                    import os
+                    threads = os.cpu_count() or 4
+                    self.model = LuxTTS(
+                        model_path=LUXTTS_HF_REPO,
+                        device="cpu",
+                        threads=min(threads, 8),
+                    )
+                else:
+                    self.model = LuxTTS(
+                        model_path=LUXTTS_HF_REPO,
+                        device=device,
+                    )
+            finally:
+                tracker_context.__exit__(None, None, None)
+
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+
+            logger.info("LuxTTS loaded successfully")
+
+        except Exception as e:
+            logger.error(f"Failed to load LuxTTS: {e}")
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        if self.model is not None:
+            del self.model
+            self.model = None
+
+            import torch
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+
+            logger.info("LuxTTS unloaded")
+
+    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.
+
+        LuxTTS uses its own encode_prompt() which runs Whisper ASR internally
+        to transcribe the reference. The reference_text parameter is not used
+        by LuxTTS itself, but we include it in the cache key for consistency.
+        """
+        await self.load_model()
+
+        # Compute cache key once for both lookup and storage
+        cache_key = ("luxtts_" + get_cache_key(audio_path, reference_text)) if use_cache else None
+
+        if cache_key:
+            cached = get_cached_voice_prompt(cache_key)
+            if cached is not None and isinstance(cached, dict):
+                return cached, True
+
+        def _encode_sync():
+            return self.model.encode_prompt(
+                prompt_audio=str(audio_path),
+                duration=5,
+                rms=0.01,
+            )
+
+        encoded = await asyncio.to_thread(_encode_sync)
+
+        if cache_key:
+            cache_voice_prompt(cache_key, encoded)
+
+        return encoded, False
+
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple reference samples.
+
+        LuxTTS doesn't have native multi-prompt support, so we concatenate
+        the audio and let encode_prompt handle the combined clip.
+        """
+        combined_audio = []
+        for path in audio_paths:
+            audio, _sr = load_audio(path, sample_rate=24000)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        combined_text = " ".join(reference_texts)
+
+        return mixed, combined_text
+
+    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 audio from text using LuxTTS.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Encoded prompt dict from encode_prompt()
+            language: Language code (LuxTTS is English-focused)
+            seed: Random seed for reproducibility
+            instruct: Not supported by LuxTTS (ignored)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model()
+
+        def _generate_sync():
+            import torch
+
+            if seed is not None:
+                torch.manual_seed(seed)
+                if torch.cuda.is_available():
+                    torch.cuda.manual_seed(seed)
+
+            wav = self.model.generate_speech(
+                text=text,
+                encode_dict=voice_prompt,
+                num_steps=4,
+                guidance_scale=3.0,
+                t_shift=0.5,
+                speed=1.0,
+                return_smooth=False,  # 48kHz output
+            )
+
+            # LuxTTS returns a tensor (may be on GPU/MPS), move to CPU first
+            audio = wav.detach().cpu().numpy().squeeze()
+            return audio, 48000
+
+        return await asyncio.to_thread(_generate_sync)

backend/backends/mlx_backend.py

@@ -5,8 +5,15 @@ MLX backend implementation for TTS and STT using mlx-audio.
 from typing import Optional, List, Tuple
 import asyncio
 import numpy as np
+import os
 from pathlib import Path
 
+# PATCH: Import and apply offline patch BEFORE any huggingface_hub usage
+# This prevents mlx_audio from making network requests when models are cached
+from ..utils.hf_offline_patch import patch_huggingface_hub_offline, ensure_original_qwen_config_cached
+patch_huggingface_hub_offline()
+ensure_original_qwen_config_cached()
+
 from . import TTSBackend, STTBackend
 from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
 from ..utils.audio import normalize_audio, load_audio
@@ -14,6 +21,12 @@ from ..utils.progress import get_progress_manager
 from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
 from ..utils.tasks import get_task_manager
 
+LANGUAGE_CODE_TO_NAME = {
+    "zh": "chinese", "en": "english", "ja": "japanese", "ko": "korean",
+    "de": "german", "fr": "french", "ru": "russian", "pt": "portuguese",
+    "es": "spanish", "it": "italian",
+}
+
 
 class MLXTTSBackend:
     """MLX-based TTS backend using mlx-audio."""
@@ -52,6 +65,47 @@ 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 +133,83 @@ class MLXTTSBackend:
     def _load_model_sync(self, model_size: str):
         """Synchronous model loading."""
         try:
-            from mlx_audio.tts import load
+            # Get model path BEFORE importing mlx_audio
-            
-            # Get model path
             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
+            # Check if model is already cached
-            task_manager = get_task_manager()
+            is_cached = self._is_model_cached(model_size)
-            task_manager.start_download(model_name)
+            
+            # 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
+            # Only track download progress if model is NOT cached
-            progress_manager.update_progress(
+            if not is_cached:
-                model_name=model_name,
+                # Start tracking download task
-                current=0,
+                task_manager.start_download(model_name)
-                total=1,
+                
-                filename="",
+                # Initialize progress state so SSE endpoint has initial data to send
-                status="downloading",
+                # 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
+            # IMPORTANT: Patch tqdm BEFORE importing mlx_audio
-            progress_callback = create_hf_progress_callback(model_name, progress_manager)
+            # Otherwise mlx_audio caches reference to original tqdm
-            tracker = HFProgressTracker(progress_callback)
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
             
-            # Use progress tracker during download
+            # PATCH: Force offline mode when model is already cached
-            with tracker.patch_download():
+            # This prevents crashes when HuggingFace is unreachable
-                # Load MLX model (downloads automatically)
+            original_hf_hub_offline = os.environ.get("HF_HUB_OFFLINE")
+            if is_cached:
+                os.environ["HF_HUB_OFFLINE"] = "1"
+                print(f"[PATCH] Model {model_size} is cached, forcing HF_HUB_OFFLINE=1 to avoid network requests")
+            
+            # Import mlx_audio AFTER patching tqdm
+            from mlx_audio.tts import load
+            
+            # Load MLX model (downloads automatically)
+            try:
                 self.model = load(model_path)
+            except Exception as load_error:
+                # If offline mode failed, try with network enabled as fallback
+                if is_cached and "offline" in str(load_error).lower():
+                    print(f"[PATCH] Offline load failed, trying with network: {load_error}")
+                    os.environ.pop("HF_HUB_OFFLINE", None)
+                    self.model = load(model_path)
+                else:
+                    raise
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+                # Restore original HF_HUB_OFFLINE setting
+                if original_hf_hub_offline is not None:
+                    os.environ["HF_HUB_OFFLINE"] = original_hf_hub_offline
+                else:
+                    os.environ.pop("HF_HUB_OFFLINE", 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:
@@ -258,7 +349,8 @@ class MLXTTSBackend:
             # MLX generate() returns a generator yielding GenerationResult objects
             audio_chunks = []
             sample_rate = 24000
-            
+            lang = LANGUAGE_CODE_TO_NAME.get(language, "auto")
+
             # Set seed if provided (MLX uses numpy random)
             if seed is not None:
                 import mlx.core as mx
@@ -286,23 +378,23 @@ class MLXTTSBackend:
                     sig = inspect.signature(self.model.generate)
                     if "ref_audio" in sig.parameters:
                         # Generate with voice cloning
-                        for result in self.model.generate(text, ref_audio=ref_audio, ref_text=ref_text):
+                        for result in self.model.generate(text, ref_audio=ref_audio, ref_text=ref_text, lang_code=lang):
                             audio_chunks.append(np.array(result.audio))
                             sample_rate = result.sample_rate
                     else:
                         # Fallback: generate without voice cloning
-                        for result in self.model.generate(text):
+                        for result in self.model.generate(text, lang_code=lang):
                             audio_chunks.append(np.array(result.audio))
                             sample_rate = result.sample_rate
                 else:
                     # No voice prompt, generate normally
-                    for result in self.model.generate(text):
+                    for result in self.model.generate(text, lang_code=lang):
                         audio_chunks.append(np.array(result.audio))
                         sample_rate = result.sample_rate
             except Exception as e:
                 # If voice cloning fails, try without it
                 print(f"Warning: Voice cloning failed, generating without voice prompt: {e}")
-                for result in self.model.generate(text):
+                for result in self.model.generate(text, lang_code=lang):
                     audio_chunks.append(np.array(result.audio))
                     sample_rate = result.sample_rate
             
@@ -321,9 +413,17 @@ class MLXTTSBackend:
         return audio, sample_rate
 
 
+WHISPER_HF_REPOS = {
+    "base": "openai/whisper-base",
+    "small": "openai/whisper-small",
+    "medium": "openai/whisper-medium",
+    "large": "openai/whisper-large-v3",
+}
+
+
 class MLXSTTBackend:
     """MLX-based STT backend using mlx-audio Whisper."""
-    
+
     def __init__(self, model_size: str = "base"):
         self.model = None
         self.model_size = model_size
@@ -332,6 +432,47 @@ 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
+            hf_repo = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + hf_repo.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.
@@ -354,55 +495,58 @@ class MLXSTTBackend:
     def _load_model_sync(self, model_size: str):
         """Synchronous model loading."""
         try:
-            # IMPORTANT: Set up progress tracking BEFORE importing mlx_audio
-            # This ensures tqdm is patched before any HuggingFace Hub imports
             progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
             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)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
 
             # Patch tqdm BEFORE importing mlx_audio
-            # This is critical because mlx_audio imports huggingface_hub which imports tqdm
-            print("[DEBUG] Starting tqdm patch BEFORE mlx_audio import")
             tracker_context = tracker.patch_download()
             tracker_context.__enter__()
-            print("[DEBUG] tqdm patched, now importing mlx_audio")
 
-            # NOW import mlx_audio - it will use our patched tqdm
+            # Import mlx_audio
             from mlx_audio.stt import load
 
             # MLX Whisper uses the standard OpenAI models
-            model_name = f"openai/whisper-{model_size}"
+            model_name = WHISPER_HF_REPOS.get(model_size, f"openai/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
+            # Only track download progress if model is NOT cached
-            progress_manager.update_progress(
+            if not is_cached:
-                model_name=progress_model_name,
+                # Start tracking download task
-                current=0,
+                task_manager.start_download(progress_model_name)
-                total=1,
+                
-                filename="",
+                # Initialize progress state so SSE endpoint has initial data to send
-                status="downloading",
+                progress_manager.update_progress(
-            )
+                    model_name=progress_model_name,
+                    current=0,
+                    total=0,
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
 
-            # Load the model (tqdm is already patched from above)
+            # 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)
             
-            self.model_size = model_size
+            # 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)
             
-            # Mark as complete
+            self.model_size = model_size
-            progress_manager.mark_complete(progress_model_name)
-            task_manager.complete_download(progress_model_name)
             
             print(f"MLX Whisper model {model_size} loaded successfully")
             

backend/backends/pytorch_backend.py

@@ -15,6 +15,12 @@ from ..utils.progress import get_progress_manager
 from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
 from ..utils.tasks import get_task_manager
 
+LANGUAGE_CODE_TO_NAME = {
+    "zh": "chinese", "en": "english", "ja": "japanese", "ko": "korean",
+    "de": "german", "fr": "french", "ru": "russian", "pt": "portuguese",
+    "es": "spanish", "it": "italian",
+}
+
 
 class PyTorchTTSBackend:
     """PyTorch-based TTS backend using Qwen3-TTS."""
@@ -29,9 +35,23 @@ class PyTorchTTSBackend:
         """Get the best available device."""
         if torch.cuda.is_available():
             return "cuda"
-        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+        # Intel Arc / Intel Xe GPU via intel-extension-for-pytorch (IPEX)
-            # MPS can have issues, use CPU for stability
+        try:
-            return "cpu"
+            import intel_extension_for_pytorch  # noqa: F401
+            if hasattr(torch, 'xpu') and torch.xpu.is_available():
+                return "xpu"
+        except ImportError:
+            pass
+        # Any GPU on Windows via DirectML (torch-directml)
+        try:
+            import torch_directml
+            if torch_directml.device_count() > 0:
+                return torch_directml.device(0)
+        except ImportError:
+            pass
+        # MPS (Apple Silicon) — kept for completeness but MLX backend is preferred
+        if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+            return "cpu"  # MPS disabled for stability; MLX backend handles Apple Silicon
         return "cpu"
     
     def is_loaded(self) -> bool:
@@ -58,6 +78,46 @@ 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.
@@ -85,20 +145,24 @@ class PyTorchTTSBackend:
     def _load_model_sync(self, model_size: str):
         """Synchronous model loading."""
         try:
-            # IMPORTANT: Set up progress tracking BEFORE importing qwen_tts
-            # This ensures tqdm is patched before any HuggingFace Hub imports
             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)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
 
             # Patch tqdm BEFORE importing qwen_tts
             tracker_context = tracker.patch_download()
             tracker_context.__enter__()
 
-            # NOW import qwen_tts - it will use our patched tqdm
+            # Import qwen_tts
             from qwen_tts import Qwen3TTSModel
 
             # Get model path (local or HuggingFace Hub ID)
@@ -106,33 +170,45 @@ class PyTorchTTSBackend:
 
             print(f"Loading TTS model {model_size} on {self.device}...")
 
-            # Start tracking download task
+            # Only track download progress if model is NOT cached
-            task_manager = get_task_manager()
+            if not is_cached:
-            task_manager.start_download(model_name)
+                # Start tracking download task
+                task_manager.start_download(model_name)
 
-            # Initialize progress state to show download has started
+                # Initialize progress state so SSE endpoint has initial data to send
-            progress_manager.update_progress(
+                progress_manager.update_progress(
-                model_name=model_name,
+                    model_name=model_name,
-                current=0,
+                    current=0,
-                total=1,  # Set to 1 initially, will be updated by callback
+                    total=0,  # Will be updated once actual total is known
-                filename="",
+                    filename="Connecting to HuggingFace...",
-                status="downloading",
+                    status="downloading",
-            )
-
-            # Load the model (tqdm is already patched from above)
-            try:
-                self.model = Qwen3TTSModel.from_pretrained(
-                    model_path,
-                    device_map=self.device,
-                    torch_dtype=torch.float32 if self.device == "cpu" else torch.bfloat16,
                 )
+
+            # Load the model (tqdm is patched, but filters out non-download progress)
+            try:
+                # Don't pass device_map on CPU: accelerate's meta-tensor mechanism
+                # causes "Cannot copy out of meta tensor" when moving to CPU.
+                # Instead load directly then call .to(device) if needed.
+                if self.device == "cpu":
+                    self.model = Qwen3TTSModel.from_pretrained(
+                        model_path,
+                        torch_dtype=torch.float32,
+                        low_cpu_mem_usage=False,
+                    )
+                else:
+                    self.model = Qwen3TTSModel.from_pretrained(
+                        model_path,
+                        device_map=self.device,
+                        torch_dtype=torch.bfloat16,
+                    )
             finally:
                 # Exit the patch context
                 tracker_context.__exit__(None, None, None)
             
-            # Mark as complete
+            # Only mark download as complete if we were tracking it
-            progress_manager.mark_complete(model_name)
+            if not is_cached:
-            task_manager.complete_download(model_name)
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
             
             self._current_model_size = model_size
             self.model_size = model_size
@@ -289,6 +365,7 @@ class PyTorchTTSBackend:
             wavs, sample_rate = self.model.generate_voice_clone(
                 text=text,
                 voice_clone_prompt=voice_prompt,
+                language=LANGUAGE_CODE_TO_NAME.get(language, "auto"),
                 instruct=instruct,
             )
             return wavs[0], sample_rate
@@ -299,9 +376,18 @@ class PyTorchTTSBackend:
         return audio, sample_rate
 
 
+WHISPER_HF_REPOS = {
+    "base": "openai/whisper-base",
+    "small": "openai/whisper-small",
+    "medium": "openai/whisper-medium",
+    "large": "openai/whisper-large-v3",
+    "turbo": "openai/whisper-large-v3-turbo",
+}
+
+
 class PyTorchSTTBackend:
     """PyTorch-based STT backend using Whisper."""
-    
+
     def __init__(self, model_size: str = "base"):
         self.model = None
         self.processor = None
@@ -312,15 +398,68 @@ class PyTorchSTTBackend:
         """Get the best available device."""
         if torch.cuda.is_available():
             return "cuda"
-        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+        # Intel Arc / Intel Xe GPU via intel-extension-for-pytorch (IPEX)
-            # MPS support for Whisper
+        try:
-            return "cpu"  # Use CPU for stability
+            import intel_extension_for_pytorch  # noqa: F401
+            if hasattr(torch, 'xpu') and torch.xpu.is_available():
+                return "xpu"
+        except ImportError:
+            pass
+        # Any GPU on Windows via DirectML (torch-directml)
+        try:
+            import torch_directml
+            if torch_directml.device_count() > 0:
+                return torch_directml.device(0)
+        except ImportError:
+            pass
+        if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+            return "cpu"  # MPS disabled for stability
         return "cpu"
     
     def is_loaded(self) -> bool:
         """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
+            hf_repo = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + hf_repo.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.
@@ -349,14 +488,18 @@ class PyTorchSTTBackend:
         """Synchronous model loading."""
         print(f"[DEBUG] _load_model_sync called for Whisper {model_size}")
         try:
-            # IMPORTANT: Set up progress tracking BEFORE importing transformers
-            # This ensures tqdm is patched before any HuggingFace Hub imports
             progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
             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)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
 
             # Patch tqdm BEFORE importing transformers
             print("[DEBUG] Starting tqdm patch BEFORE transformers import")
@@ -364,31 +507,29 @@ class PyTorchSTTBackend:
             tracker_context.__enter__()
             print("[DEBUG] tqdm patched, now importing transformers")
 
-            # NOW import transformers - it will use our patched tqdm
+            # Import transformers
             from transformers import WhisperProcessor, WhisperForConditionalGeneration
 
-            model_name = f"openai/whisper-{model_size}"
+            model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
             print(f"[DEBUG] Model name: {model_name}")
 
-            # Start tracking download task
-            task_manager = get_task_manager()
-            task_manager.start_download(progress_model_name)
-            print(f"[DEBUG] Task manager started download")
-
             print(f"Loading Whisper model {model_size} on {self.device}...")
 
-            # Initialize progress state to show download has started
+            # Only track download progress if model is NOT cached
-            print(f"[DEBUG] Calling update_progress...")
+            if not is_cached:
-            progress_manager.update_progress(
+                # Start tracking download task
-                model_name=progress_model_name,
+                task_manager.start_download(progress_model_name)
-                current=0,
-                total=1,  # Set to 1 initially, will be updated by callback
-                filename="",
-                status="downloading",
-            )
-            print(f"[DEBUG] update_progress called, listeners: {len(progress_manager._listeners.get(progress_model_name, []))}")
 
-            # Load models (tqdm is already patched from above)
+                # 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)
@@ -396,13 +537,14 @@ class PyTorchSTTBackend:
                 # 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:
@@ -457,21 +599,20 @@ class PyTorchSTTBackend:
             )
             inputs = inputs.to(self.device)
             
-            # Set language if provided
+            # Generate transcription
-            forced_decoder_ids = None
+            # If language is provided, force it; otherwise let Whisper auto-detect
+            generate_kwargs = {}
             if language:
-                # Support all languages from frontend: en, zh, ja, ko, de, fr, ru, pt, es, it
-                # Whisper supports these and many more
                 forced_decoder_ids = self.processor.get_decoder_prompt_ids(
                     language=language,
                     task="transcribe",
                 )
+                generate_kwargs["forced_decoder_ids"] = forced_decoder_ids
             
-            # Generate transcription
             with torch.no_grad():
                 predicted_ids = self.model.generate(
                     inputs["input_features"],
-                    forced_decoder_ids=forced_decoder_ids,
+                    **generate_kwargs,
                 )
             
             # Decode

backend/build_binary.py

@@ -1,8 +1,13 @@
 """
 PyInstaller build script for creating standalone Python server binary.
+
+Usage:
+    python build_binary.py           # Build default (CPU) server binary
+    python build_binary.py --cuda    # Build CUDA-enabled server binary
 """
 
 import PyInstaller.__main__
+import argparse
 import os
 import platform
 from pathlib import Path
@@ -13,15 +18,22 @@ def is_apple_silicon():
     return platform.system() == "Darwin" and platform.machine() == "arm64"
 
 
-def build_server():
+def build_server(cuda=False):
-    """Build Python server as standalone binary."""
+    """Build Python server as standalone binary.
+
+    Args:
+        cuda: If True, build with CUDA support and name the binary
+              voicebox-server-cuda instead of voicebox-server.
+    """
     backend_dir = Path(__file__).parent
 
+    binary_name = 'voicebox-server-cuda' if cuda else 'voicebox-server'
+
     # PyInstaller arguments
     args = [
         'server.py',  # Use server.py as entry point instead of main.py
         '--onefile',
-        '--name', 'voicebox-server',
+        '--name', binary_name,
     ]
 
     # Add local qwen_tts path if specified (for editable installs)
@@ -49,6 +61,7 @@ def build_server():
         '--hidden-import', 'backend.utils.progress',
         '--hidden-import', 'backend.utils.hf_progress',
         '--hidden-import', 'backend.utils.validation',
+        '--hidden-import', 'backend.cuda_download',
         '--hidden-import', 'torch',
         '--hidden-import', 'transformers',
         '--hidden-import', 'fastapi',
@@ -70,8 +83,16 @@ def build_server():
         '--collect-submodules', 'jaraco',
     ])
 
-    # Add MLX-specific imports if building on Apple Silicon
+    # Add CUDA-specific hidden imports
-    if is_apple_silicon():
+    if cuda:
+        print("Building with CUDA support")
+        args.extend([
+            '--hidden-import', 'torch.cuda',
+            '--hidden-import', 'torch.backends.cudnn',
+        ])
+
+    # Add MLX-specific imports if building on Apple Silicon (never for CUDA builds)
+    if is_apple_silicon() and not cuda:
         print("Building for Apple Silicon - including MLX dependencies")
         args.extend([
             '--hidden-import', 'backend.backends.mlx_backend',
@@ -83,11 +104,15 @@ def build_server():
             '--hidden-import', 'mlx_audio.stt',
             '--collect-submodules', 'mlx',
             '--collect-submodules', 'mlx_audio',
-            # Collect MLX data files including Metal shader libraries (.metallib)
+            # Use --collect-all so PyInstaller bundles both data files AND
-            '--collect-data', 'mlx',
+            # native shared libraries (.dylib, .metallib) for MLX.
-            '--collect-data', 'mlx_audio',
+            # Previously only --collect-data was used, which caused MLX to
+            # raise OSError at runtime inside the bundled binary because
+            # the Metal shader libraries were missing.
+            '--collect-all', 'mlx',
+            '--collect-all', 'mlx_audio',
         ])
-    else:
+    elif not cuda:
         print("Building for non-Apple Silicon platform - PyTorch only")
 
     args.extend([
@@ -101,8 +126,15 @@ def build_server():
     # Run PyInstaller
     PyInstaller.__main__.run(args)
     
-    print(f"Binary built in {backend_dir / 'dist' / 'voicebox-server'}")
+    print(f"Binary built in {backend_dir / 'dist' / binary_name}")
 
 
 if __name__ == '__main__':
-    build_server()
+    parser = argparse.ArgumentParser(description="Build voicebox-server binary")
+    parser.add_argument(
+        '--cuda',
+        action='store_true',
+        help="Build CUDA-enabled binary (voicebox-server-cuda)",
+    )
+    cli_args = parser.parse_args()
+    build_server(cuda=cli_args.cuda)

backend/config.py

@@ -4,8 +4,17 @@ Configuration module for voicebox backend.
 Handles data directory configuration for production bundling.
 """
 
+import os
 from pathlib import Path
 
+# Allow users to override the HuggingFace model download directory.
+# Set VOICEBOX_MODELS_DIR to an absolute path before starting the server.
+# This sets HF_HUB_CACHE so all huggingface_hub downloads go to that path.
+_custom_models_dir = os.environ.get("VOICEBOX_MODELS_DIR")
+if _custom_models_dir:
+    os.environ["HF_HUB_CACHE"] = _custom_models_dir
+    print(f"[config] Model download path set to: {_custom_models_dir}")
+
 # Default data directory (used in development)
 _data_dir = Path("data")
 

backend/cuda_download.py

@@ -0,0 +1,198 @@
+"""
+CUDA backend binary download, assembly, and verification.
+
+Downloads split parts of the CUDA-enabled voicebox-server binary from
+GitHub Releases, reassembles them, verifies integrity via SHA-256,
+and places the binary in the app's data directory for use on next
+backend restart.
+"""
+
+import hashlib
+import logging
+import os
+import sys
+from pathlib import Path
+from typing import Optional
+
+from .config import get_data_dir
+from .utils.progress import get_progress_manager
+from . import __version__
+
+logger = logging.getLogger(__name__)
+
+GITHUB_RELEASES_URL = "https://github.com/jamiepine/voicebox/releases/download"
+
+PROGRESS_KEY = "cuda-backend"
+
+
+def get_backends_dir() -> Path:
+    """Directory where downloaded backend binaries are stored."""
+    d = get_data_dir() / "backends"
+    d.mkdir(parents=True, exist_ok=True)
+    return d
+
+
+def get_cuda_binary_name() -> str:
+    """Platform-specific CUDA binary filename."""
+    if sys.platform == "win32":
+        return "voicebox-server-cuda.exe"
+    return "voicebox-server-cuda"
+
+
+def get_cuda_binary_path() -> Optional[Path]:
+    """Return path to CUDA binary if it exists."""
+    p = get_backends_dir() / get_cuda_binary_name()
+    if p.exists():
+        return p
+    return None
+
+
+def is_cuda_active() -> bool:
+    """Check if the current process is the CUDA binary.
+
+    The CUDA binary sets this env var on startup (see server.py).
+    """
+    return os.environ.get("VOICEBOX_BACKEND_VARIANT") == "cuda"
+
+
+def get_cuda_status() -> dict:
+    """Get current CUDA backend status for the API."""
+    progress_manager = get_progress_manager()
+    cuda_path = get_cuda_binary_path()
+    progress = progress_manager.get_progress(PROGRESS_KEY)
+
+    return {
+        "available": cuda_path is not None,
+        "active": is_cuda_active(),
+        "binary_path": str(cuda_path) if cuda_path else None,
+        "downloading": progress is not None and progress.get("status") == "downloading",
+        "download_progress": progress,
+    }
+
+
+async def download_cuda_binary(version: Optional[str] = None):
+    """Download the CUDA backend binary from GitHub Releases.
+
+    Downloads split parts listed in a manifest file, concatenates them,
+    and verifies the SHA-256 checksum for integrity. Atomic write
+    (temp file -> rename).
+
+    Args:
+        version: Version tag (e.g. "v0.2.0"). Defaults to current app version.
+    """
+    import httpx
+
+    if version is None:
+        version = f"v{__version__}"
+
+    progress = get_progress_manager()
+    binary_name = get_cuda_binary_name()
+    dest_dir = get_backends_dir()
+    final_path = dest_dir / binary_name
+    temp_path = dest_dir / f"{binary_name}.download"
+
+    # Clean up any leftover partial download
+    if temp_path.exists():
+        temp_path.unlink()
+
+    logger.info(f"Starting CUDA backend download for {version}")
+    progress.update_progress(
+        PROGRESS_KEY, current=0, total=0,
+        filename="Fetching manifest...", status="downloading",
+    )
+
+    base_url = f"{GITHUB_RELEASES_URL}/{version}"
+    stem = Path(binary_name).stem  # voicebox-server-cuda
+
+    try:
+        async with httpx.AsyncClient(follow_redirects=True, timeout=30.0) as client:
+            # Fetch the manifest (list of split part filenames)
+            manifest_url = f"{base_url}/{stem}.manifest"
+            manifest_resp = await client.get(manifest_url)
+            manifest_resp.raise_for_status()
+            parts = [p.strip() for p in manifest_resp.text.strip().splitlines() if p.strip()]
+
+            if not parts:
+                raise ValueError("Empty manifest — no split parts found")
+
+            logger.info(f"Found {len(parts)} split parts to download")
+
+            # Fetch expected checksum (optional — for integrity verification)
+            expected_sha = None
+            try:
+                sha_url = f"{base_url}/{stem}.sha256"
+                sha_resp = await client.get(sha_url)
+                if sha_resp.status_code == 200:
+                    # Format: "sha256hex  filename\n"
+                    expected_sha = sha_resp.text.strip().split()[0]
+                    logger.info(f"Expected SHA-256: {expected_sha[:16]}...")
+            except Exception as e:
+                logger.warning(f"Could not fetch checksum file — skipping verification: {e}")
+
+            # Download and concatenate parts
+            total_downloaded = 0
+            with open(temp_path, "wb") as f:
+                for i, part_name in enumerate(parts):
+                    part_url = f"{base_url}/{part_name}"
+                    logger.info(f"Downloading part {i + 1}/{len(parts)}: {part_name}")
+
+                    async with client.stream("GET", part_url) as response:
+                        response.raise_for_status()
+                        async for chunk in response.aiter_bytes(chunk_size=1024 * 1024):
+                            f.write(chunk)
+                            total_downloaded += len(chunk)
+                            progress.update_progress(
+                                PROGRESS_KEY, current=total_downloaded, total=0,
+                                filename=f"Part {i + 1}/{len(parts)}",
+                                status="downloading",
+                            )
+
+        # Verify integrity if checksum was available
+        if expected_sha:
+            progress.update_progress(
+                PROGRESS_KEY, current=total_downloaded, total=total_downloaded,
+                filename="Verifying integrity...", status="downloading",
+            )
+            sha256 = hashlib.sha256()
+            with open(temp_path, "rb") as f:
+                while True:
+                    chunk = f.read(1024 * 1024)
+                    if not chunk:
+                        break
+                    sha256.update(chunk)
+
+            actual = sha256.hexdigest()
+            if actual != expected_sha:
+                raise ValueError(
+                    f"Integrity check failed: expected {expected_sha[:16]}..., "
+                    f"got {actual[:16]}..."
+                )
+            logger.info(f"Integrity verified: {actual[:16]}...")
+
+        # Atomic move into place (replace handles existing target on all platforms)
+        temp_path.replace(final_path)
+
+        # Make executable on Unix
+        if sys.platform != "win32":
+            final_path.chmod(0o755)
+
+        logger.info(f"CUDA backend downloaded to {final_path}")
+        progress.mark_complete(PROGRESS_KEY)
+
+    except Exception as e:
+        # Clean up on failure
+        if temp_path.exists():
+            temp_path.unlink()
+        logger.error(f"CUDA backend download failed: {e}")
+        progress.mark_error(PROGRESS_KEY, str(e))
+        raise
+
+
+async def delete_cuda_binary() -> bool:
+    """Delete the downloaded CUDA binary. Returns True if deleted."""
+    path = get_cuda_binary_path()
+    if path and path.exists():
+        path.unlink()
+        logger.info(f"Deleted CUDA binary: {path}")
+        return True
+    return False

backend/database.py

@@ -45,10 +45,14 @@ class Generation(Base):
     profile_id = Column(String, ForeignKey("profiles.id"), nullable=False)
     text = Column(Text, nullable=False)
     language = Column(String, default="en")
-    audio_path = Column(String, nullable=False)
+    audio_path = Column(String, nullable=True)
-    duration = Column(Float, nullable=False)
+    duration = Column(Float, nullable=True)
     seed = Column(Integer)
     instruct = Column(Text)
+    engine = Column(String, default="qwen")
+    model_size = Column(String, nullable=True)
+    status = Column(String, default="completed")  # generating, completed, failed
+    error = Column(Text, nullable=True)
     created_at = Column(DateTime, default=datetime.utcnow)
 
 
@@ -288,6 +292,36 @@ def _run_migrations(engine):
                 conn.commit()
                 print("Added avatar_path column to profiles")
 
+    # Migration: Add status and error columns to generations table
+    if 'generations' in inspector.get_table_names():
+        columns = {col['name'] for col in inspector.get_columns('generations')}
+        if 'status' not in columns:
+            print("Migrating generations: adding status column")
+            with engine.connect() as conn:
+                conn.execute(text("ALTER TABLE generations ADD COLUMN status VARCHAR DEFAULT 'completed'"))
+                conn.commit()
+                print("Added status column to generations")
+        if 'error' not in columns:
+            print("Migrating generations: adding error column")
+            with engine.connect() as conn:
+                conn.execute(text("ALTER TABLE generations ADD COLUMN error TEXT"))
+                conn.commit()
+                print("Added error column to generations")
+        if 'engine' not in columns:
+            print("Migrating generations: adding engine column")
+            with engine.connect() as conn:
+                conn.execute(text("ALTER TABLE generations ADD COLUMN engine VARCHAR DEFAULT 'qwen'"))
+                conn.commit()
+                print("Added engine column to generations")
+        # Re-read columns after engine migration (variable name shadows outer `engine`)
+        columns = {col['name'] for col in inspector.get_columns('generations')}
+        if 'model_size' not in columns:
+            print("Migrating generations: adding model_size column")
+            with engine.connect() as conn:
+                conn.execute(text("ALTER TABLE generations ADD COLUMN model_size VARCHAR"))
+                conn.commit()
+                print("Added model_size column to generations")
+
 
 def get_db():
     """Get database session (generator for dependency injection)."""

backend/history.py

@@ -29,6 +29,10 @@ async def create_generation(
     seed: Optional[int],
     db: Session,
     instruct: Optional[str] = None,
+    generation_id: Optional[str] = None,
+    status: str = "completed",
+    engine: Optional[str] = "qwen",
+    model_size: Optional[str] = None,
 ) -> GenerationResponse:
     """
     Create a new generation history entry.
@@ -42,12 +46,16 @@ async def create_generation(
         seed: Random seed used (if any)
         db: Database session
         instruct: Natural language instruction used (if any)
+        generation_id: Pre-assigned ID (for async generation flow)
+        status: Generation status (generating, completed, failed)
+        engine: TTS engine used (qwen, luxtts, chatterbox, chatterbox_turbo)
+        model_size: Model size variant (1.7B, 0.6B) — only relevant for qwen
 
     Returns:
         Created generation entry
     """
     db_generation = DBGeneration(
-        id=str(uuid.uuid4()),
+        id=generation_id or str(uuid.uuid4()),
         profile_id=profile_id,
         text=text,
         language=language,
@@ -55,6 +63,9 @@ async def create_generation(
         duration=duration,
         seed=seed,
         instruct=instruct,
+        engine=engine,
+        model_size=model_size,
+        status=status,
         created_at=datetime.utcnow(),
     )
 
@@ -65,6 +76,32 @@ async def create_generation(
     return GenerationResponse.model_validate(db_generation)
 
 
+async def update_generation_status(
+    generation_id: str,
+    status: str,
+    db: Session,
+    audio_path: Optional[str] = None,
+    duration: Optional[float] = None,
+    error: Optional[str] = None,
+) -> Optional[GenerationResponse]:
+    """Update the status of a generation (used by async generation flow)."""
+    generation = db.query(DBGeneration).filter_by(id=generation_id).first()
+    if not generation:
+        return None
+
+    generation.status = status
+    if audio_path is not None:
+        generation.audio_path = audio_path
+    if duration is not None:
+        generation.duration = duration
+    if error is not None:
+        generation.error = error
+
+    db.commit()
+    db.refresh(generation)
+    return GenerationResponse.model_validate(generation)
+
+
 async def get_generation(
     generation_id: str,
     db: Session,
@@ -143,6 +180,10 @@ async def list_generations(
             duration=generation.duration,
             seed=generation.seed,
             instruct=generation.instruct,
+            engine=generation.engine or "qwen",
+            model_size=generation.model_size,
+            status=generation.status or "completed",
+            error=generation.error,
             created_at=generation.created_at,
         ))
     

backend/models.py

@@ -11,7 +11,7 @@ class VoiceProfileCreate(BaseModel):
     """Request model for creating a voice profile."""
     name: str = Field(..., min_length=1, max_length=100)
     description: Optional[str] = Field(None, max_length=500)
-    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it)$")
+    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it|he|ar|da|el|fi|hi|ms|nl|no|pl|sv|sw|tr)$")
 
 
 class VoiceProfileResponse(BaseModel):
@@ -52,11 +52,15 @@ class ProfileSampleResponse(BaseModel):
 class GenerationRequest(BaseModel):
     """Request model for voice generation."""
     profile_id: str
-    text: str = Field(..., min_length=1, max_length=5000)
+    text: str = Field(..., min_length=1, max_length=50000)
-    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it)$")
+    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it|he)$")
     seed: Optional[int] = Field(None, ge=0)
     model_size: Optional[str] = Field(default="1.7B", pattern="^(1\\.7B|0\\.6B)$")
     instruct: Optional[str] = Field(None, max_length=500)
+    engine: Optional[str] = Field(default="qwen", pattern="^(qwen|luxtts|chatterbox|chatterbox_turbo)$")
+    max_chunk_chars: int = Field(default=800, ge=100, le=5000, description="Max characters per chunk for long text splitting")
+    crossfade_ms: int = Field(default=50, ge=0, le=500, description="Crossfade duration in ms between chunks (0 for hard cut)")
+    normalize: bool = Field(default=True, description="Normalize output audio volume")
 
 
 class GenerationResponse(BaseModel):
@@ -65,10 +69,14 @@ class GenerationResponse(BaseModel):
     profile_id: str
     text: str
     language: str
-    audio_path: str
+    audio_path: Optional[str] = None
-    duration: float
+    duration: Optional[float] = None
-    seed: Optional[int]
+    seed: Optional[int] = None
-    instruct: Optional[str]
+    instruct: Optional[str] = None
+    engine: Optional[str] = "qwen"
+    model_size: Optional[str] = None
+    status: str = "completed"
+    error: Optional[str] = None
     created_at: datetime
 
     class Config:
@@ -90,10 +98,14 @@ class HistoryResponse(BaseModel):
     profile_name: str
     text: str
     language: str
-    audio_path: str
+    audio_path: Optional[str] = None
-    duration: float
+    duration: Optional[float] = None
-    seed: Optional[int]
+    seed: Optional[int] = None
-    instruct: Optional[str]
+    instruct: Optional[str] = None
+    engine: Optional[str] = "qwen"
+    model_size: Optional[str] = None
+    status: str = "completed"
+    error: Optional[str] = None
     created_at: datetime
 
     class Config:
@@ -127,13 +139,32 @@ class HealthResponse(BaseModel):
     gpu_type: Optional[str] = None  # GPU type (CUDA, MPS, or None)
     vram_used_mb: Optional[float] = None
     backend_type: Optional[str] = None  # Backend type (mlx or pytorch)
+    backend_variant: Optional[str] = None  # Binary variant (cpu or cuda)
+
+
+class DirectoryCheck(BaseModel):
+    """Health status for a single directory."""
+    path: str
+    exists: bool
+    writable: bool
+    error: Optional[str] = None
+
+
+class FilesystemHealthResponse(BaseModel):
+    """Response model for filesystem health check."""
+    healthy: bool
+    disk_free_mb: Optional[float] = None
+    disk_total_mb: Optional[float] = None
+    directories: List[DirectoryCheck]
 
 
 class ModelStatus(BaseModel):
     """Response model for model status."""
     model_name: str
     display_name: str
+    hf_repo_id: Optional[str] = None  # HuggingFace repository ID
     downloaded: bool
+    downloading: bool = False  # True if download is in progress
     size_mb: Optional[float] = None
     loaded: bool = False
 
@@ -148,11 +179,21 @@ class ModelDownloadRequest(BaseModel):
     model_name: str
 
 
+class ModelMigrateRequest(BaseModel):
+    """Request model for migrating models to a new directory."""
+    destination: str
+
+
 class ActiveDownloadTask(BaseModel):
     """Response model for active download task."""
     model_name: str
     status: str
     started_at: datetime
+    error: Optional[str] = None
+    progress: Optional[float] = None  # 0-100 percentage
+    current: Optional[int] = None     # bytes downloaded
+    total: Optional[int] = None       # total bytes
+    filename: Optional[str] = None    # current file being downloaded
 
 
 class ActiveGenerationTask(BaseModel):

backend/platform_detect.py

@@ -19,15 +19,17 @@ def is_apple_silicon() -> bool:
 def get_backend_type() -> Literal["mlx", "pytorch"]:
     """
     Detect the best backend for the current platform.
-    
+
     Returns:
-        "mlx" on Apple Silicon (if MLX is available), "pytorch" otherwise
+        "mlx" on Apple Silicon (if MLX is available and functional), "pytorch" otherwise
     """
     if is_apple_silicon():
         try:
-            import mlx
+            import mlx.core  # noqa: F401 — triggers native lib loading
             return "mlx"
-        except ImportError:
+        except (ImportError, OSError, RuntimeError):
-            # MLX not installed, fallback to PyTorch
+            # MLX not installed, or native libraries failed to load inside a
+            # PyInstaller bundle (OSError on missing .dylib / .metallib).
+            # Fall through to PyTorch.
             return "pytorch"
     return "pytorch"

backend/profiles.py

@@ -38,14 +38,22 @@ async def create_profile(
 ) -> VoiceProfileResponse:
     """
     Create a new voice profile.
-    
+
     Args:
         data: Profile creation data
         db: Database session
-        
+
     Returns:
         Created profile
+
+    Raises:
+        ValueError: If a profile with the same name already exists
     """
+    # Check if profile name already exists
+    existing_profile = db.query(DBVoiceProfile).filter_by(name=data.name).first()
+    if existing_profile:
+        raise ValueError(f"A profile with the name '{data.name}' already exists. Please choose a different name.")
+
     # Create profile in database
     db_profile = DBVoiceProfile(
         id=str(uuid.uuid4()),
@@ -55,15 +63,15 @@ async def create_profile(
         created_at=datetime.utcnow(),
         updated_at=datetime.utcnow(),
     )
-    
+
     db.add(db_profile)
     db.commit()
     db.refresh(db_profile)
-    
+
     # Create profile directory
     profile_dir = _get_profiles_dir() / db_profile.id
     profile_dir.mkdir(parents=True, exist_ok=True)
-    
+
     return VoiceProfileResponse.model_validate(db_profile)
 
 
@@ -191,28 +199,37 @@ async def update_profile(
 ) -> Optional[VoiceProfileResponse]:
     """
     Update a voice profile.
-    
+
     Args:
         profile_id: Profile ID
         data: Updated profile data
         db: Database session
-        
+
     Returns:
         Updated profile or None if not found
+
+    Raises:
+        ValueError: If a profile with the same name already exists (different profile)
     """
     profile = db.query(DBVoiceProfile).filter_by(id=profile_id).first()
     if not profile:
         return None
-    
+
+    # Check if the new name conflicts with another profile
+    if profile.name != data.name:
+        existing_profile = db.query(DBVoiceProfile).filter_by(name=data.name).first()
+        if existing_profile:
+            raise ValueError(f"A profile with the name '{data.name}' already exists. Please choose a different name.")
+
     # Update fields
     profile.name = data.name
     profile.description = data.description
     profile.language = data.language
     profile.updated_at = datetime.utcnow()
-    
+
     db.commit()
     db.refresh(profile)
-    
+
     return VoiceProfileResponse.model_validate(profile)
 
 
@@ -327,6 +344,7 @@ async def create_voice_prompt_for_profile(
     profile_id: str,
     db: Session,
     use_cache: bool = True,
+    engine: str = "qwen",
 ) -> dict:
     """
     Create a combined voice prompt from all samples in a profile.
@@ -335,17 +353,20 @@ async def create_voice_prompt_for_profile(
         profile_id: Profile ID
         db: Database session
         use_cache: Whether to use cached prompts
+        engine: TTS engine to create prompt for ("qwen" or "luxtts")
 
     Returns:
         Voice prompt dictionary
     """
+    from .backends import get_tts_backend_for_engine
+
     # Get all samples for profile
     samples = db.query(DBProfileSample).filter_by(profile_id=profile_id).all()
 
     if not samples:
         raise ValueError(f"No samples found for profile {profile_id}")
 
-    tts_model = get_tts_model()
+    tts_model = get_tts_backend_for_engine(engine)
 
     if len(samples) == 1:
         # Single sample - use directly

backend/requirements.txt

@@ -9,15 +9,38 @@ alembic>=1.13.0
 
 # ML models
 torch>=2.1.0
-transformers>=4.36.0
+transformers>=4.36.0,<=4.57.6
 accelerate>=0.26.0
 huggingface_hub>=0.20.0
 qwen-tts>=0.0.5
 
+# LuxTTS (voice cloning engine)
+# piper-phonemize needs custom index (no PyPI wheels)
+--find-links https://k2-fsa.github.io/icefall/piper_phonemize.html
+# linacodec is a git-only dep of Zipvoice (uv-only source, pip can't resolve it)
+linacodec @ git+https://github.com/ysharma3501/LinaCodec.git
+Zipvoice @ git+https://github.com/ysharma3501/LuxTTS.git
+
+# Chatterbox TTS sub-dependencies (chatterbox-tts itself is installed
+# --no-deps in the setup script because it pins numpy<1.26 / torch==2.6
+# which are incompatible with Python 3.12+)
+conformer>=0.3.2
+diffusers>=0.29.0
+omegaconf
+pykakasi
+resemble-perth>=1.0.1
+s3tokenizer
+spacy-pkuseg
+pyloudnorm
+
 # Audio processing
 librosa>=0.10.0
 soundfile>=0.12.0
 numpy>=1.24.0
+numba>=0.60.0,<0.61.0
+
+# HTTP client (for CUDA backend download)
+httpx>=0.27.0
 
 # Utilities
 python-multipart>=0.0.6

backend/server.py

@@ -64,7 +64,29 @@ if __name__ == "__main__":
             default=None,
             help="Data directory for database, profiles, and generated audio",
         )
+        parser.add_argument(
+            "--version",
+            action="store_true",
+            help="Print version and exit",
+        )
         args = parser.parse_args()
+
+        if args.version:
+            from backend import __version__
+            print(f"voicebox-server {__version__}")
+            sys.exit(0)
+
+        # Detect backend variant from binary name
+        # voicebox-server-cuda → sets VOICEBOX_BACKEND_VARIANT=cuda
+        import os
+        binary_name = os.path.basename(sys.executable).lower()
+        if "cuda" in binary_name:
+            os.environ["VOICEBOX_BACKEND_VARIANT"] = "cuda"
+            logger.info("Backend variant: CUDA")
+        else:
+            os.environ["VOICEBOX_BACKEND_VARIANT"] = "cpu"
+            logger.info("Backend variant: CPU")
+
         logger.info(f"Parsed arguments: host={args.host}, port={args.port}, data_dir={args.data_dir}")
 
         # Set data directory if provided

backend/stories.py

@@ -270,11 +270,14 @@ async def add_item_to_story(
             generation_created_at=generation.created_at,
         )
 
+    # Get track from data or default to 0
+    track = data.track if data.track is not None else 0
+
     # Calculate start_time_ms if not provided
     if data.start_time_ms is not None:
         start_time_ms = data.start_time_ms
     else:
-        # Find the maximum end time (start_time_ms + duration_ms) of existing items
+        # Find the maximum end time on the target track only
         existing_items = db.query(
             DBStoryItem,
             DBGeneration
@@ -282,11 +285,11 @@ async def add_item_to_story(
             DBGeneration,
             DBStoryItem.generation_id == DBGeneration.id
         ).filter(
-            DBStoryItem.story_id == story_id
+            DBStoryItem.story_id == story_id,
+            DBStoryItem.track == track,
         ).all()
         
         if not existing_items:
-            # First item starts at 0
             start_time_ms = 0
         else:
             max_end_time_ms = 0
@@ -297,9 +300,6 @@ async def add_item_to_story(
             # Add 200ms gap after the last item
             start_time_ms = max_end_time_ms + 200
 
-    # Get track from data or default to 0
-    track = data.track if data.track is not None else 0
-
     # Create item
     item = DBStoryItem(
         id=str(uuid.uuid4()),

backend/tests/README.md

@@ -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

backend/tests/__init__.py

@@ -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.
+"""

backend/tests/test_cors.py

@@ -0,0 +1,162 @@
+"""
+Tests for CORS origin restrictions.
+
+Validates that the CORS middleware only allows known local origins
+and respects the VOICEBOX_CORS_ORIGINS environment variable.
+
+Uses a minimal FastAPI app that mirrors the exact CORS configuration
+from backend/main.py, so tests run without heavy ML dependencies.
+
+Usage:
+    pip install httpx pytest fastapi starlette
+    python -m pytest backend/tests/test_cors.py -v
+"""
+
+import os
+import pytest
+from unittest.mock import patch
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from starlette.testclient import TestClient
+
+
+def _build_app(env_origins: str = "") -> FastAPI:
+    """
+    Build a minimal FastAPI app with the same CORS logic as backend/main.py.
+
+    This mirrors the exact code in main.py so the test validates the real
+    configuration without needing torch/numpy/transformers installed.
+    """
+    app = FastAPI()
+
+    _default_origins = [
+        "http://localhost:5173",
+        "http://127.0.0.1:5173",
+        "http://localhost:17493",
+        "http://127.0.0.1:17493",
+        "tauri://localhost",
+        "https://tauri.localhost",
+    ]
+    _cors_origins = _default_origins + [o.strip() for o in env_origins.split(",") if o.strip()]
+
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=_cors_origins,
+        allow_credentials=True,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    @app.get("/health")
+    async def health():
+        return {"status": "ok"}
+
+    return app
+
+
+@pytest.fixture()
+def client():
+    return TestClient(_build_app())
+
+
+@pytest.fixture()
+def client_with_custom_origins():
+    return TestClient(_build_app("https://custom.example.com,https://other.example.com"))
+
+
+def _get_with_origin(client: TestClient, origin: str) -> dict:
+    """Send a GET with Origin header, return response headers."""
+    response = client.get("/health", headers={"Origin": origin})
+    return dict(response.headers)
+
+
+def _preflight(client: TestClient, origin: str) -> dict:
+    """Send CORS preflight OPTIONS request, return response headers."""
+    response = client.options(
+        "/health",
+        headers={
+            "Origin": origin,
+            "Access-Control-Request-Method": "GET",
+        },
+    )
+    return dict(response.headers)
+
+
+class TestCORSDefaultOrigins:
+    """CORS should allow known local origins and block everything else."""
+
+    @pytest.mark.parametrize("origin", [
+        "http://localhost:5173",
+        "http://127.0.0.1:5173",
+        "http://localhost:17493",
+        "http://127.0.0.1:17493",
+        "tauri://localhost",
+        "https://tauri.localhost",
+    ])
+    def test_allowed_origins(self, client, origin):
+        headers = _get_with_origin(client, origin)
+        assert headers.get("access-control-allow-origin") == origin
+
+    @pytest.mark.parametrize("origin", [
+        "http://evil.com",
+        "http://localhost:9999",
+        "https://attacker.example.com",
+        "null",
+    ])
+    def test_blocked_origins(self, client, origin):
+        headers = _get_with_origin(client, origin)
+        assert "access-control-allow-origin" not in headers
+
+    def test_preflight_allowed(self, client):
+        headers = _preflight(client, "http://localhost:5173")
+        assert headers.get("access-control-allow-origin") == "http://localhost:5173"
+
+    def test_preflight_blocked(self, client):
+        headers = _preflight(client, "http://evil.com")
+        assert "access-control-allow-origin" not in headers
+
+    def test_credentials_header_present(self, client):
+        headers = _get_with_origin(client, "http://localhost:5173")
+        assert headers.get("access-control-allow-credentials") == "true"
+
+
+class TestCORSCustomOrigins:
+    """VOICEBOX_CORS_ORIGINS env var should extend the allowlist."""
+
+    def test_custom_origin_allowed(self, client_with_custom_origins):
+        headers = _get_with_origin(client_with_custom_origins, "https://custom.example.com")
+        assert headers.get("access-control-allow-origin") == "https://custom.example.com"
+
+    def test_other_custom_origin_allowed(self, client_with_custom_origins):
+        headers = _get_with_origin(client_with_custom_origins, "https://other.example.com")
+        assert headers.get("access-control-allow-origin") == "https://other.example.com"
+
+    def test_default_origins_still_work(self, client_with_custom_origins):
+        headers = _get_with_origin(client_with_custom_origins, "http://localhost:5173")
+        assert headers.get("access-control-allow-origin") == "http://localhost:5173"
+
+    def test_unlisted_origin_still_blocked(self, client_with_custom_origins):
+        headers = _get_with_origin(client_with_custom_origins, "http://evil.com")
+        assert "access-control-allow-origin" not in headers
+
+
+class TestCORSEnvVarParsing:
+    """Edge cases for VOICEBOX_CORS_ORIGINS parsing."""
+
+    def test_empty_env_var(self):
+        app = _build_app("")
+        client = TestClient(app)
+        headers = _get_with_origin(client, "http://evil.com")
+        assert "access-control-allow-origin" not in headers
+
+    def test_whitespace_trimmed(self):
+        app = _build_app("  https://spaced.example.com  ")
+        client = TestClient(app)
+        headers = _get_with_origin(client, "https://spaced.example.com")
+        assert headers.get("access-control-allow-origin") == "https://spaced.example.com"
+
+    def test_trailing_comma_ignored(self):
+        app = _build_app("https://one.example.com,")
+        client = TestClient(app)
+        headers = _get_with_origin(client, "https://one.example.com")
+        assert headers.get("access-control-allow-origin") == "https://one.example.com"

backend/tests/test_generation_download.py

@@ -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())

backend/tests/test_profile_duplicate_names.py

@@ -0,0 +1,217 @@
+"""
+Tests for profile duplicate name validation.
+
+This test suite verifies that the application correctly handles
+duplicate profile names and provides user-friendly error messages.
+"""
+
+import pytest
+import tempfile
+import shutil
+from pathlib import Path
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+
+# Add parent directory to path to import backend modules
+import sys
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from database import Base, VoiceProfile as DBVoiceProfile
+from models import VoiceProfileCreate
+from profiles import create_profile, update_profile
+
+
+@pytest.fixture
+def test_db():
+    """Create a temporary test database."""
+    # Create temporary directory for test database
+    temp_dir = tempfile.mkdtemp()
+    db_path = Path(temp_dir) / "test.db"
+
+    # Create engine and session
+    engine = create_engine(f"sqlite:///{db_path}")
+    Base.metadata.create_all(bind=engine)
+    SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+
+    db = SessionLocal()
+
+    yield db
+
+    # Cleanup
+    db.close()
+    shutil.rmtree(temp_dir)
+
+
+@pytest.fixture
+def mock_profiles_dir(monkeypatch, tmp_path):
+    """Mock the profiles directory to use a temporary path."""
+    import profiles
+    monkeypatch.setattr(profiles, '_get_profiles_dir', lambda: tmp_path)
+    return tmp_path
+
+
+@pytest.mark.asyncio
+async def test_create_profile_duplicate_name_raises_error(test_db, mock_profiles_dir):
+    """Test that creating a profile with a duplicate name raises a ValueError."""
+    # Create first profile
+    profile_data_1 = VoiceProfileCreate(
+        name="Test Profile",
+        description="First profile",
+        language="en"
+    )
+
+    profile_1 = await create_profile(profile_data_1, test_db)
+    assert profile_1.name == "Test Profile"
+
+    # Try to create second profile with same name
+    profile_data_2 = VoiceProfileCreate(
+        name="Test Profile",
+        description="Second profile",
+        language="en"
+    )
+
+    with pytest.raises(ValueError) as exc_info:
+        await create_profile(profile_data_2, test_db)
+
+    # Verify error message is user-friendly
+    assert "already exists" in str(exc_info.value)
+    assert "Test Profile" in str(exc_info.value)
+    assert "choose a different name" in str(exc_info.value).lower()
+
+
+@pytest.mark.asyncio
+async def test_create_profile_different_names_succeeds(test_db, mock_profiles_dir):
+    """Test that creating profiles with different names succeeds."""
+    # Create first profile
+    profile_data_1 = VoiceProfileCreate(
+        name="Profile One",
+        description="First profile",
+        language="en"
+    )
+
+    profile_1 = await create_profile(profile_data_1, test_db)
+    assert profile_1.name == "Profile One"
+
+    # Create second profile with different name
+    profile_data_2 = VoiceProfileCreate(
+        name="Profile Two",
+        description="Second profile",
+        language="en"
+    )
+
+    profile_2 = await create_profile(profile_data_2, test_db)
+    assert profile_2.name == "Profile Two"
+
+    # Verify both profiles exist
+    assert profile_1.id != profile_2.id
+
+
+@pytest.mark.asyncio
+async def test_update_profile_to_duplicate_name_raises_error(test_db, mock_profiles_dir):
+    """Test that updating a profile to a duplicate name raises a ValueError."""
+    # Create two profiles with different names
+    profile_data_1 = VoiceProfileCreate(
+        name="Profile A",
+        description="First profile",
+        language="en"
+    )
+    profile_1 = await create_profile(profile_data_1, test_db)
+
+    profile_data_2 = VoiceProfileCreate(
+        name="Profile B",
+        description="Second profile",
+        language="en"
+    )
+    profile_2 = await create_profile(profile_data_2, test_db)
+
+    # Try to update profile_2 to use profile_1's name
+    update_data = VoiceProfileCreate(
+        name="Profile A",  # Duplicate name
+        description="Updated description",
+        language="en"
+    )
+
+    with pytest.raises(ValueError) as exc_info:
+        await update_profile(profile_2.id, update_data, test_db)
+
+    # Verify error message is user-friendly
+    assert "already exists" in str(exc_info.value)
+    assert "Profile A" in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_update_profile_keep_same_name_succeeds(test_db, mock_profiles_dir):
+    """Test that updating a profile while keeping the same name succeeds."""
+    # Create profile
+    profile_data = VoiceProfileCreate(
+        name="My Profile",
+        description="Original description",
+        language="en"
+    )
+    profile = await create_profile(profile_data, test_db)
+
+    # Update profile with same name but different description
+    update_data = VoiceProfileCreate(
+        name="My Profile",  # Same name
+        description="Updated description",
+        language="en"
+    )
+
+    updated_profile = await update_profile(profile.id, update_data, test_db)
+
+    # Verify update succeeded
+    assert updated_profile is not None
+    assert updated_profile.id == profile.id
+    assert updated_profile.name == "My Profile"
+    assert updated_profile.description == "Updated description"
+
+
+@pytest.mark.asyncio
+async def test_update_profile_to_new_unique_name_succeeds(test_db, mock_profiles_dir):
+    """Test that updating a profile to a new unique name succeeds."""
+    # Create profile
+    profile_data = VoiceProfileCreate(
+        name="Original Name",
+        description="Profile description",
+        language="en"
+    )
+    profile = await create_profile(profile_data, test_db)
+
+    # Update profile with new unique name
+    update_data = VoiceProfileCreate(
+        name="New Unique Name",
+        description="Updated description",
+        language="en"
+    )
+
+    updated_profile = await update_profile(profile.id, update_data, test_db)
+
+    # Verify update succeeded
+    assert updated_profile is not None
+    assert updated_profile.id == profile.id
+    assert updated_profile.name == "New Unique Name"
+
+
+@pytest.mark.asyncio
+async def test_case_sensitive_names_allowed(test_db, mock_profiles_dir):
+    """Test that profile names are case-sensitive (e.g., 'Test' and 'test' are different)."""
+    # Create profile with lowercase name
+    profile_data_1 = VoiceProfileCreate(
+        name="test profile",
+        description="Lowercase",
+        language="en"
+    )
+    profile_1 = await create_profile(profile_data_1, test_db)
+
+    # Create profile with different case
+    profile_data_2 = VoiceProfileCreate(
+        name="Test Profile",
+        description="Title case",
+        language="en"
+    )
+    profile_2 = await create_profile(profile_data_2, test_db)
+
+    # Both should succeed since SQLite unique constraint is case-sensitive by default
+    assert profile_1.name == "test profile"
+    assert profile_2.name == "Test Profile"
+    assert profile_1.id != profile_2.id

backend/tests/test_progress.py

@@ -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)

backend/tests/test_qwen_download.py

@@ -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)

backend/tests/test_whisper_download.py

@@ -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())

backend/tts.py

@@ -32,11 +32,3 @@ def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes:
     sf.write(buffer, audio, sample_rate, format="WAV")
     buffer.seek(0)
     return buffer.read()
-
-
-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()

backend/utils/audio.py

@@ -70,14 +70,133 @@ def save_audio(
     sample_rate: int = 24000,
 ) -> None:
     """
-    Save audio file.
+    Save audio file with atomic write and error handling.
-    
+
+    Writes to a temporary file first, then atomically renames to the
+    target path.  This prevents corrupted/partial WAV files if the
+    process is interrupted mid-write.
+
     Args:
         audio: Audio array
         path: Output path
         sample_rate: Sample rate
+
+    Raises:
+        OSError: If file cannot be written
     """
-    sf.write(path, audio, sample_rate)
+    from pathlib import Path
+    import os
+
+    temp_path = f"{path}.tmp"
+    try:
+        # Ensure parent directory exists
+        Path(path).parent.mkdir(parents=True, exist_ok=True)
+
+        # Write to temporary file first (explicit format since .tmp
+        # extension is not recognised by soundfile)
+        sf.write(temp_path, audio, sample_rate, format='WAV')
+
+        # Atomic rename to final path
+        os.replace(temp_path, path)
+
+    except Exception as e:
+        # Clean up temp file on failure
+        try:
+            if Path(temp_path).exists():
+                Path(temp_path).unlink()
+        except Exception:
+            pass  # Best effort cleanup
+
+        raise OSError(f"Failed to save audio to {path}: {e}") from e
+
+
+def trim_tts_output(
+    audio: np.ndarray,
+    sample_rate: int = 24000,
+    frame_ms: int = 20,
+    silence_threshold_db: float = -40.0,
+    min_silence_ms: int = 200,
+    max_internal_silence_ms: int = 1000,
+    fade_ms: int = 30,
+) -> np.ndarray:
+    """
+    Trim trailing silence and post-silence hallucination from TTS output.
+
+    Chatterbox sometimes produces ``[speech][silence][hallucinated noise]``.
+    This detects internal silence gaps longer than *max_internal_silence_ms*
+    and cuts the audio at that boundary, then trims trailing silence and
+    applies a short cosine fade-out.
+
+    Args:
+        audio: Input audio array (mono float32)
+        sample_rate: Sample rate in Hz
+        frame_ms: Frame size for RMS energy calculation
+        silence_threshold_db: dB threshold below which a frame is silence
+        min_silence_ms: Minimum trailing silence to keep
+        max_internal_silence_ms: Cut after any silence gap longer than this
+        fade_ms: Cosine fade-out duration in ms
+
+    Returns:
+        Trimmed audio array
+    """
+    frame_len = int(sample_rate * frame_ms / 1000)
+    if frame_len == 0 or len(audio) < frame_len:
+        return audio
+
+    n_frames = len(audio) // frame_len
+    threshold_linear = 10 ** (silence_threshold_db / 20)
+
+    # Compute per-frame RMS
+    rms = np.array(
+        [
+            np.sqrt(np.mean(audio[i * frame_len : (i + 1) * frame_len] ** 2))
+            for i in range(n_frames)
+        ]
+    )
+    is_speech = rms >= threshold_linear
+
+    # Find first speech frame
+    first_speech = 0
+    for i, s in enumerate(is_speech):
+        if s:
+            first_speech = max(0, i - 1)  # keep 1 frame padding
+            break
+
+    # Walk forward from first speech; cut at long internal silence gaps
+    max_silence_frames = int(max_internal_silence_ms / frame_ms)
+    consecutive_silence = 0
+    cut_frame = n_frames
+
+    for i in range(first_speech, n_frames):
+        if is_speech[i]:
+            consecutive_silence = 0
+        else:
+            consecutive_silence += 1
+            if consecutive_silence >= max_silence_frames:
+                cut_frame = i - consecutive_silence + 1
+                break
+
+    # Trim trailing silence from the cut point
+    min_silence_frames = int(min_silence_ms / frame_ms)
+    end_frame = cut_frame
+    while end_frame > first_speech and not is_speech[end_frame - 1]:
+        end_frame -= 1
+    # Keep a short tail
+    end_frame = min(end_frame + min_silence_frames, cut_frame)
+
+    # Convert frames back to samples
+    start_sample = first_speech * frame_len
+    end_sample = min(end_frame * frame_len, len(audio))
+
+    trimmed = audio[start_sample:end_sample].copy()
+
+    # Cosine fade-out
+    fade_samples = int(sample_rate * fade_ms / 1000)
+    if fade_samples > 0 and len(trimmed) > fade_samples:
+        fade = np.cos(np.linspace(0, np.pi / 2, fade_samples)) ** 2
+        trimmed[-fade_samples:] *= fade
+
+    return trimmed
 
 
 def validate_reference_audio(

backend/utils/chunked_tts.py

@@ -0,0 +1,302 @@
+"""
+Chunked TTS generation utilities.
+
+Splits long text into sentence-boundary chunks, generates audio per-chunk
+via any TTSBackend, and concatenates with crossfade.  All logic is
+engine-agnostic — it wraps the standard ``TTSBackend.generate()`` interface.
+
+Short text (≤ max_chunk_chars) uses the single-shot fast path with zero
+overhead.
+"""
+
+import logging
+import re
+from typing import List, Tuple
+
+import numpy as np
+
+logger = logging.getLogger("voicebox.chunked-tts")
+
+# Default chunk size in characters.  Can be overridden per-request via
+# the ``max_chunk_chars`` field on GenerationRequest.
+DEFAULT_MAX_CHUNK_CHARS = 800
+
+# Common abbreviations that should NOT be treated as sentence endings.
+# Lowercase for case-insensitive matching.
+_ABBREVIATIONS = frozenset(
+    {
+        "mr",
+        "mrs",
+        "ms",
+        "dr",
+        "prof",
+        "sr",
+        "jr",
+        "st",
+        "ave",
+        "blvd",
+        "inc",
+        "ltd",
+        "corp",
+        "dept",
+        "est",
+        "approx",
+        "vs",
+        "etc",
+        "e.g",
+        "i.e",
+        "a.m",
+        "p.m",
+        "u.s",
+        "u.s.a",
+        "u.k",
+    }
+)
+
+# Paralinguistic tags used by Chatterbox Turbo.  The splitter must never
+# cut inside one of these.
+_PARA_TAG_RE = re.compile(r"\[[^\]]*\]")
+
+
+# ---------------------------------------------------------------------------
+# Text splitting
+# ---------------------------------------------------------------------------
+
+
+def split_text_into_chunks(text: str, max_chars: int = DEFAULT_MAX_CHUNK_CHARS) -> List[str]:
+    """Split *text* at natural boundaries into chunks of at most *max_chars*.
+
+    Priority: sentence-end (``.!?`` not preceded by an abbreviation and not
+    inside brackets) → clause boundary (``;:,—``) → whitespace → hard cut.
+
+    Paralinguistic tags like ``[laugh]`` are treated as atomic and will not
+    be split across chunks.
+    """
+    text = text.strip()
+    if not text:
+        return []
+    if len(text) <= max_chars:
+        return [text]
+
+    chunks: List[str] = []
+    remaining = text
+
+    while remaining:
+        remaining = remaining.lstrip()
+        if not remaining:
+            break
+        if len(remaining) <= max_chars:
+            chunks.append(remaining)
+            break
+
+        segment = remaining[:max_chars]
+
+        # Try to split at the last real sentence ending
+        split_pos = _find_last_sentence_end(segment)
+        if split_pos == -1:
+            split_pos = _find_last_clause_boundary(segment)
+        if split_pos == -1:
+            split_pos = segment.rfind(" ")
+        if split_pos == -1:
+            # Absolute fallback: hard cut but avoid splitting inside a tag
+            split_pos = _safe_hard_cut(segment, max_chars)
+
+        chunk = remaining[: split_pos + 1].strip()
+        if chunk:
+            chunks.append(chunk)
+        remaining = remaining[split_pos + 1 :]
+
+    return chunks
+
+
+def _find_last_sentence_end(text: str) -> int:
+    """Return the index of the last sentence-ending punctuation in *text*.
+
+    Skips periods that follow common abbreviations (``Dr.``, ``Mr.``, etc.)
+    and periods inside bracket tags (``[laugh]``).  Also handles CJK
+    sentence-ending punctuation (``。！？``).
+    """
+    best = -1
+    # ASCII sentence ends
+    for m in re.finditer(r"[.!?](?:\s|$)", text):
+        pos = m.start()
+        char = text[pos]
+        # Skip periods after abbreviations
+        if char == ".":
+            # Walk backwards to find the preceding word
+            word_start = pos - 1
+            while word_start >= 0 and text[word_start].isalpha():
+                word_start -= 1
+            word = text[word_start + 1 : pos].lower()
+            if word in _ABBREVIATIONS:
+                continue
+            # Skip decimal numbers (digit immediately before the period)
+            if word_start >= 0 and text[word_start].isdigit():
+                continue
+        # Skip if we're inside a bracket tag
+        if _inside_bracket_tag(text, pos):
+            continue
+        best = pos
+    # CJK sentence-ending punctuation
+    for m in re.finditer(r"[\u3002\uff01\uff1f]", text):
+        if m.start() > best:
+            best = m.start()
+    return best
+
+
+def _find_last_clause_boundary(text: str) -> int:
+    """Return the index of the last clause-boundary punctuation."""
+    best = -1
+    for m in re.finditer(r"[;:,\u2014](?:\s|$)", text):
+        pos = m.start()
+        # Skip if inside a bracket tag
+        if _inside_bracket_tag(text, pos):
+            continue
+        best = pos
+    return best
+
+
+def _inside_bracket_tag(text: str, pos: int) -> bool:
+    """Return True if *pos* falls inside a ``[...]`` tag."""
+    for m in _PARA_TAG_RE.finditer(text):
+        if m.start() < pos < m.end():
+            return True
+    return False
+
+
+def _safe_hard_cut(segment: str, max_chars: int) -> int:
+    """Find a hard-cut position that doesn't split a ``[tag]``."""
+    cut = max_chars - 1
+    # Check if the cut falls inside a bracket tag; if so, move before it
+    for m in _PARA_TAG_RE.finditer(segment):
+        if m.start() < cut < m.end():
+            return m.start() - 1 if m.start() > 0 else cut
+    return cut
+
+
+# ---------------------------------------------------------------------------
+# Audio concatenation
+# ---------------------------------------------------------------------------
+
+
+def concatenate_audio_chunks(
+    chunks: List[np.ndarray],
+    sample_rate: int,
+    crossfade_ms: int = 50,
+) -> np.ndarray:
+    """Concatenate audio arrays with a short crossfade to eliminate clicks.
+
+    Each chunk is expected to be a 1-D float32 ndarray at *sample_rate* Hz.
+    """
+    if not chunks:
+        return np.array([], dtype=np.float32)
+    if len(chunks) == 1:
+        return chunks[0]
+
+    crossfade_samples = int(sample_rate * crossfade_ms / 1000)
+    result = np.array(chunks[0], dtype=np.float32, copy=True)
+
+    for chunk in chunks[1:]:
+        if len(chunk) == 0:
+            continue
+        overlap = min(crossfade_samples, len(result), len(chunk))
+        if overlap > 0:
+            fade_out = np.linspace(1.0, 0.0, overlap, dtype=np.float32)
+            fade_in = np.linspace(0.0, 1.0, overlap, dtype=np.float32)
+            result[-overlap:] = result[-overlap:] * fade_out + chunk[:overlap] * fade_in
+            result = np.concatenate([result, chunk[overlap:]])
+        else:
+            result = np.concatenate([result, chunk])
+
+    return result
+
+
+# ---------------------------------------------------------------------------
+# Engine-agnostic chunked generation
+# ---------------------------------------------------------------------------
+
+
+async def generate_chunked(
+    backend,
+    text: str,
+    voice_prompt: dict,
+    language: str = "en",
+    seed: int | None = None,
+    instruct: str | None = None,
+    max_chunk_chars: int = DEFAULT_MAX_CHUNK_CHARS,
+    crossfade_ms: int = 50,
+    trim_fn=None,
+) -> Tuple[np.ndarray, int]:
+    """Generate audio with automatic chunking for long text.
+
+    For text shorter than *max_chunk_chars* this is a thin wrapper around
+    ``backend.generate()`` with zero overhead.
+
+    For longer text the input is split at natural sentence boundaries,
+    each chunk is generated independently, optionally trimmed (useful for
+    Chatterbox engines that hallucinate trailing noise), and the results
+    are concatenated with a crossfade (or hard cut if *crossfade_ms* is 0).
+
+    Parameters
+    ----------
+    backend : TTSBackend
+        Any backend implementing the ``generate()`` protocol.
+    text : str
+        Input text (may be arbitrarily long).
+    voice_prompt, language, seed, instruct
+        Forwarded to ``backend.generate()`` verbatim.
+    max_chunk_chars : int
+        Maximum characters per chunk (default 800).
+    crossfade_ms : int
+        Crossfade duration in milliseconds between chunks.  0 for a hard
+        cut with no overlap (default 50).
+    trim_fn : callable | None
+        Optional ``(audio, sample_rate) -> audio`` post-processing
+        function applied to each chunk before concatenation (e.g.
+        ``trim_tts_output`` for Chatterbox engines).
+
+    Returns
+    -------
+    (audio, sample_rate) : Tuple[np.ndarray, int]
+    """
+    chunks = split_text_into_chunks(text, max_chunk_chars)
+
+    if len(chunks) <= 1:
+        # Short text — single-shot fast path
+        audio, sample_rate = await backend.generate(
+            text, voice_prompt, language, seed, instruct,
+        )
+        if trim_fn is not None:
+            audio = trim_fn(audio, sample_rate)
+        return audio, sample_rate
+
+    # Long text — chunked generation
+    logger.info(
+        "Splitting %d chars into %d chunks (max %d chars each)",
+        len(text), len(chunks), max_chunk_chars,
+    )
+    audio_chunks: List[np.ndarray] = []
+    sample_rate: int | None = None
+
+    for i, chunk_text in enumerate(chunks):
+        logger.info(
+            "Generating chunk %d/%d (%d chars)",
+            i + 1, len(chunks), len(chunk_text),
+        )
+        # Vary the seed per chunk to avoid correlated RNG artefacts,
+        # but keep it deterministic so the same (text, seed) pair
+        # always produces the same output.
+        chunk_seed = (seed + i) if seed is not None else None
+
+        chunk_audio, chunk_sr = await backend.generate(
+            chunk_text, voice_prompt, language, chunk_seed, instruct,
+        )
+        if trim_fn is not None:
+            chunk_audio = trim_fn(chunk_audio, chunk_sr)
+
+        audio_chunks.append(np.asarray(chunk_audio, dtype=np.float32))
+        if sample_rate is None:
+            sample_rate = chunk_sr
+
+    audio = concatenate_audio_chunks(audio_chunks, sample_rate, crossfade_ms=crossfade_ms)
+    return audio, sample_rate

backend/utils/hf_offline_patch.py

@@ -0,0 +1,100 @@
+"""
+Monkey patch for huggingface_hub to force offline mode with cached models.
+This prevents mlx_audio from making network requests when models are already downloaded.
+"""
+
+import os
+from pathlib import Path
+from typing import Optional, Union
+
+
+def patch_huggingface_hub_offline():
+    """
+    Monkey-patch huggingface_hub to force offline mode.
+    This must be called BEFORE importing mlx_audio.
+    """
+    try:
+        import huggingface_hub
+        from huggingface_hub import constants as hf_constants
+        from huggingface_hub.file_download import _try_to_load_from_cache
+        
+        # Store original function
+        original_try_load = _try_to_load_from_cache
+        
+        def _patched_try_to_load_from_cache(
+            repo_id: str,
+            filename: str,
+            cache_dir: Union[str, Path, None] = None,
+            revision: Optional[str] = None,
+            repo_type: Optional[str] = None,
+        ):
+            """
+            Patched version that forces offline mode.
+            Returns None if not cached (instead of making network request).
+            """
+            # Always use the original function, but we're already in HF_HUB_OFFLINE mode
+            result = original_try_load(
+                repo_id=repo_id,
+                filename=filename,
+                cache_dir=cache_dir,
+                revision=revision,
+                repo_type=repo_type,
+            )
+            
+            if result is None:
+                # File not in cache - log this for debugging
+                cache_path = Path(hf_constants.HF_HUB_CACHE) / f"models--{repo_id.replace('/', '--')}"
+                print(f"[HF_PATCH] File not cached: {repo_id}/{filename}")
+                print(f"[HF_PATCH] Expected at: {cache_path}")
+            else:
+                print(f"[HF_PATCH] Cache hit: {repo_id}/{filename}")
+            
+            return result
+        
+        # Replace the function
+        import huggingface_hub.file_download as fd
+        fd._try_to_load_from_cache = _patched_try_to_load_from_cache
+        
+        print("[HF_PATCH] huggingface_hub patched for offline mode")
+        
+    except ImportError:
+        print("[HF_PATCH] huggingface_hub not found, skipping patch")
+    except Exception as e:
+        print(f"[HF_PATCH] Error patching huggingface_hub: {e}")
+
+
+def ensure_original_qwen_config_cached():
+    """
+    The MLX community model is based on the original Qwen model.
+    mlx_audio may try to fetch config from the original repo.
+    We need to ensure that config is available in the cache.
+    """
+    from huggingface_hub import constants as hf_constants
+    
+    # Original Qwen model that mlx_audio might reference
+    original_repo = "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
+    mlx_repo = "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16"
+    
+    cache_dir = Path(hf_constants.HF_HUB_CACHE)
+    
+    original_path = cache_dir / f"models--{original_repo.replace('/', '--')}"
+    mlx_path = cache_dir / f"models--{mlx_repo.replace('/', '--')}"
+    
+    # If original repo cache doesn't exist but MLX does, create a symlink or copy config
+    if not original_path.exists() and mlx_path.exists():
+        print(f"[HF_PATCH] Original repo not cached, but MLX version is")
+        print(f"[HF_PATCH] Creating symlink from {original_repo} -> {mlx_repo}")
+        
+        try:
+            # Create a symlink so the cache lookup succeeds
+            original_path.parent.mkdir(parents=True, exist_ok=True)
+            original_path.symlink_to(mlx_path, target_is_directory=True)
+            print(f"[HF_PATCH] Symlink created successfully")
+        except Exception as e:
+            print(f"[HF_PATCH] Could not create symlink: {e}")
+
+
+# Auto-apply patch when module is imported
+if os.environ.get("VOICEBOX_OFFLINE_PATCH", "1") != "0":
+    patch_huggingface_hub_offline()
+    ensure_original_qwen_config_cached()

backend/utils/hf_progress.py

@@ -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."""
@@ -31,7 +33,6 @@ class HFProgressTracker:
             """A tqdm subclass that reports progress to our tracker."""
 
             def __init__(self, *args, **kwargs):
-                print(f"[DEBUG TrackedTqdm] __init__ called with desc: {kwargs.get('desc', '')}")
                 # Extract filename from desc before passing to parent
                 desc = kwargs.get("desc", "")
                 if not desc and args:
@@ -80,7 +81,6 @@ class HFProgressTracker:
                     }
             
             def update(self, n=1):
-                print(f"[DEBUG TrackedTqdm] update called with n={n}")
                 result = super().update(n)
 
                 # Report progress
@@ -91,6 +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
@@ -99,6 +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(
@@ -109,6 +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:
@@ -120,13 +181,11 @@ class HFProgressTracker:
     @contextmanager
     def patch_download(self):
         """Context manager to patch tqdm for progress tracking."""
-        print("[DEBUG HFProgressTracker] patch_download called")
         try:
             import tqdm as tqdm_module
 
             # Store original tqdm class
             self._original_tqdm_class = tqdm_module.tqdm
-            print(f"[DEBUG HFProgressTracker] Original tqdm class: {self._original_tqdm_class}")
             
             # Reset totals
             with self._lock:
@@ -139,39 +198,89 @@ class HFProgressTracker:
             
             # Create our tracked tqdm class
             tracked_tqdm = self._create_tracked_tqdm_class()
-            print(f"[DEBUG HFProgressTracker] Created TrackedTqdm class: {tracked_tqdm}")
 
             # Patch tqdm.tqdm
             tqdm_module.tqdm = tracked_tqdm
-            print(f"[DEBUG HFProgressTracker] Patched tqdm.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"):
                 self._original_tqdm_auto = tqdm_module.auto.tqdm
                 tqdm_module.auto.tqdm = tracked_tqdm
-                print(f"[DEBUG HFProgressTracker] Patched tqdm.auto.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"):
+                        for attr_name in tqdm_attr_names:
-                            attr = getattr(module, "tqdm")
+                            if hasattr(module, attr_name):
-                            # Only patch if it's the original tqdm class (not already patched)
+                                attr = getattr(module, attr_name)
-                            if attr is self._original_tqdm_class or (
+                                # Only patch if it's a tqdm class (not already patched)
-                                hasattr(attr, "__name__") and attr.__name__ == "tqdm"
+                                is_tqdm_class = (
-                            ):
+                                    attr is self._original_tqdm_class or 
-                                self._patched_modules[module_name] = attr
+                                    (self._original_tqdm_auto and attr is self._original_tqdm_auto) or
-                                setattr(module, "tqdm", tracked_tqdm)
+                                    (hasattr(attr, "__name__") and attr.__name__ == "tqdm" and 
-                                patched_count += 1
+                                     hasattr(attr, "update"))  # tqdm classes have update method
-                                print(f"[DEBUG HFProgressTracker] Patched {module_name}.tqdm")
+                                )
+                                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
-            print(f"[DEBUG HFProgressTracker] Patched {patched_count} modules in sys.modules")
+            
+            # 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
             
@@ -189,15 +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
 
@@ -205,13 +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."""
+        """Progress callback.
-        if total > 0:
+        
-            progress_manager.update_progress(
+        Note: We send updates even when total=0 (unknown) to provide feedback
-                model_name=model_name,
+        during the "incomplete total" phase of huggingface_hub downloads.
-                current=downloaded,
+        The frontend handles total=0 gracefully.
-                total=total,
+        """
-                filename=filename or "",
+        progress_manager.update_progress(
-                status="downloading",
+            model_name=model_name,
-            )
+            current=downloaded,
+            total=total,
+            filename=filename or "",
+            status="downloading",
+        )
     return callback

backend/utils/progress.py

@@ -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."""
@@ -67,6 +73,10 @@ 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 +86,17 @@ 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,
@@ -90,25 +108,38 @@ class ProgressManager:
             "timestamp": datetime.now().isoformat(),
         }
 
-        print(f"[DEBUG] update_progress called: {model_name}, {progress_pct:.1f}%")
+        # Thread-safe update of progress dict (always update internal state)
-
-        # Thread-safe update of progress dict
         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, []))
-        print(f"[DEBUG] Listener count for {model_name}: {listener_count}")
-        print(f"[DEBUG] All listeners: {list(self._listeners.keys())}")
-        print(f"[DEBUG] Main loop set: {self._main_loop is not None}")
-        if self._main_loop:
-            print(f"[DEBUG] Main loop running: {self._main_loop.is_running()}")
 
         if listener_count > 0:
             logger.debug(f"Notifying {listener_count} listeners for {model_name}: {progress_pct:.1f}% ({filename})")
-            print(f"[DEBUG] About to notify listeners...")
             self._notify_listeners_threadsafe(model_name, progress_data)
-            print(f"[DEBUG] Notified listeners")
         else:
             logger.debug(f"No listeners for {model_name}, progress update stored: {progress_pct:.1f}%")
     

backend/utils/tasks.py

@@ -72,6 +72,15 @@ class TaskManager:
         """Get all active generations."""
         return list(self._active_generations.values())
     
+    def cancel_download(self, model_name: str) -> bool:
+        """Cancel/dismiss a download task (removes it from active list)."""
+        return self._active_downloads.pop(model_name, None) is not None
+
+    def clear_all(self) -> None:
+        """Clear all download and generation tasks."""
+        self._active_downloads.clear()
+        self._active_generations.clear()
+
     def is_download_active(self, model_name: str) -> bool:
         """Check if a download is active."""
         return model_name in self._active_downloads

backend/voicebox-server.spec

@@ -6,8 +6,13 @@ 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.stt']
 datas += collect_data_files('qwen_tts')
-datas += collect_data_files('mlx')
+# Use collect_all (not collect_data_files) so native .dylib and .metallib
-datas += collect_data_files('mlx_audio')
+# files are bundled as binaries, not data. Without this, MLX raises OSError
+# when loading Metal shaders inside the PyInstaller bundle.
+from PyInstaller.utils.hooks import collect_all as _collect_all
+_mlx_datas, _mlx_bins, _mlx_hidden = _collect_all('mlx')
+_mlxa_datas, _mlxa_bins, _mlxa_hidden = _collect_all('mlx_audio')
+datas += _mlx_datas + _mlxa_datas
 datas += copy_metadata('qwen-tts')
 hiddenimports += collect_submodules('qwen_tts')
 hiddenimports += collect_submodules('jaraco')
@@ -18,7 +23,7 @@ hiddenimports += collect_submodules('mlx_audio')
 a = Analysis(
     ['server.py'],
     pathex=[],
-    binaries=[],
+    binaries=_mlx_bins + _mlxa_bins,
     datas=datas,
     hiddenimports=hiddenimports,
     hookspath=[],

bun.lock

@@ -4,6 +4,10 @@
   "workspaces": {
     "": {
       "name": "voicebox",
+      "dependencies": {
+        "loaders.css": "^0.1.2",
+        "react-loaders": "^3.0.1",
+      },
       "devDependencies": {
         "@biomejs/biome": "2.3.12",
         "@types/node": "^20.0.0",
@@ -13,7 +17,7 @@
     },
     "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",
@@ -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": "^4.0.0",
         "@types/react": "^18.3.0",
         "@types/react-dom": "^18.3.0",
         "@typescript-eslint/eslint-plugin": "^7.0.0",
@@ -673,6 +682,8 @@
 
     "class-variance-authority": ["[email protected]", "", { "dependencies": { "clsx": "^2.1.1" } }, "sha512-Ka+9Trutv7G8M6WT6SeiRWz792K5qEqIGEGzXKhAE6xOWAY6pPH8U+9IY3oCMv6kqTmLsv7Xh/2w2RigkePMsg=="],
 
+    "classnames": ["[email protected]", "", {}, "sha512-saHYOzhIQs6wy2sVxTM6bUDsQO4F50V9RQ22qBpEdCW+I+/Wmke2HOl6lS6dTpdxVhb88/I6+Hs+438c3lfUow=="],
+
     "client-only": ["[email protected]", "", {}, "sha512-IV3Ou0jSMzZrd3pZ48nLkT9DA7Ag1pnPzaiQhpW7c3RbcqqzvzzVu+L8gfqMp/8IM2MQtSiqaCxrrcfu8I8rMA=="],
 
     "clsx": ["[email protected]", "", {}, "sha512-eYm0QWBtUrBWZWG0d386OGAw16Z995PiOVo2B7bjWSbHedGl5e0ZWaq65kOGgUSNesEIDkB9ISbTg/JK9dhCZA=="],
@@ -869,6 +880,8 @@
 
     "lines-and-columns": ["[email protected]", "", {}, "sha512-7ylylesZQ/PV29jhEDl3Ufjo6ZX7gCqJr5F7PKrqc93v7fzSymt1BpwEU8nAUXs8qzzvqhbjhK5QZg6Mt/HkBg=="],
 
+    "loaders.css": ["[email protected]", "", {}, "sha512-Rhowlq24ey1VOeor+3wYOt9+MjaxBOJm1u4KlQgNC3+0xJ0LS4wq4iG57D/BPzvuD/7HHDGQOWJ+81oR2EI9bQ=="],
+
     "locate-path": ["[email protected]", "", { "dependencies": { "p-locate": "^5.0.0" } }, "sha512-iPZK6eYjbxRu3uB4/WZ3EsEIMJFMqAoopl3R+zuq0UjcAm/MO6KCweDgPfP3elTztoKP3KtnVHxTn2NHBSDVUw=="],
 
     "lodash.merge": ["[email protected]", "", {}, "sha512-0KpjqXRVvrYyCsX1swR/XTK0va6VQkQM6MNo7PqW77ByjAhoARA8EfrP1N4+KlKj8YS0ZUCtRT/YUuhyYDujIQ=="],
@@ -955,6 +968,8 @@
 
     "prelude-ls": ["[email protected]", "", {}, "sha512-vkcDPrRZo1QZLbn5RLGPpg/WmIQ65qoWWhcGKf/b5eplkkarX0m9z8ppCat4mlOqUsWpyNuYgO3VRyrYHSzX5g=="],
 
+    "prop-types": ["[email protected]", "", { "dependencies": { "loose-envify": "^1.4.0", "object-assign": "^4.1.1", "react-is": "^16.13.1" } }, "sha512-oj87CgZICdulUohogVAR7AjlC0327U4el4L6eAvOqCeudMDVU0NThNaV+b9Df4dXgSP1gXMTnPdhfe/2qDH5cg=="],
+
     "punycode": ["[email protected]", "", {}, "sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg=="],
 
     "queue-microtask": ["[email protected]", "", {}, "sha512-NuaNSa6flKT5JaSYQzJok04JzTL1CA6aGhv5rfLW3PgqA+M2ChpZQnAC8h8i4ZFkBS8X5RqkDBHA7r4hej3K9A=="],
@@ -965,6 +980,10 @@
 
     "react-hook-form": ["[email protected]", "", { "peerDependencies": { "react": "^16.8.0 || ^17 || ^18 || ^19" } }, "sha512-9SUJKCGKo8HUSsCO+y0CtqkqI5nNuaDqTxyqPsZPqIwudpj4rCrAz/jZV+jn57bx5gtZKOh3neQu94DXMc+w5w=="],
 
+    "react-is": ["[email protected]", "", {}, "sha512-24e6ynE2H+OKt4kqsOvNd8kBpV65zoxbA4BVsEOB3ARVWQki/DHzaUoC5KuON/BiccDaCCTZBuOcfZs70kR8bQ=="],
+
+    "react-loaders": ["[email protected]", "", { "dependencies": { "classnames": "^2.2.3" }, "peerDependencies": { "prop-types": ">=15.6.0", "react": ">=15" } }, "sha512-4igMNqs9Fb3d4Z+0UHIGQNJsw/37gX0nUO8QxupnEKRn1dtyYC1LGwk5GuaoDciMQCQc/MmPwb4Fn6ZfdoX1FQ=="],
+
     "react-refresh": ["[email protected]", "", {}, "sha512-z6F7K9bV85EfseRCp2bzrpyQ0Gkw1uLoCel9XBVWPg/TjRj94SkJzUTGfOa4bs7iJvBWtQG0Wq7wnI0syw3EBQ=="],
 
     "react-remove-scroll": ["[email protected]", "", { "dependencies": { "react-remove-scroll-bar": "^2.3.7", "react-style-singleton": "^2.2.3", "tslib": "^2.1.0", "use-callback-ref": "^1.3.3", "use-sidecar": "^1.1.3" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-Iqb9NjCCTt6Hf+vOdNIZGdTiH1QSqr27H/Ek9sv/a97gfueI/5h1s3yRi1nngzMUaOOToin5dI1dXKdXiF+u0Q=="],

docker-compose.yml

@@ -0,0 +1,41 @@
+services:
+  voicebox:
+    build: .
+    container_name: voicebox
+    restart: unless-stopped
+
+    ports:
+      # Bind to localhost only for security
+      - "127.0.0.1:17493:17493"
+
+    volumes:
+      # Bind-mount for generated audio (customize the host path as needed)
+      # Host side:      ./output/
+      # Container side: /app/data/generations/
+      - ./output:/app/data/generations
+
+      # Named volume for profiles, DB, cache (persists across container restarts)
+      - voicebox-data:/app/data
+
+      # HuggingFace model cache (so models aren't re-downloaded on rebuild)
+      - huggingface-cache:/home/voicebox/.cache/huggingface
+
+    environment:
+      - LOG_LEVEL=info
+
+    networks:
+      - voicebox-net
+
+    deploy:
+      resources:
+        limits:
+          cpus: '4'
+          memory: 8G
+
+networks:
+  voicebox-net:
+    driver: bridge
+
+volumes:
+  voicebox-data:
+  huggingface-cache:

docs/PR-ACCESSIBILITY.md

@@ -0,0 +1,70 @@
+# Accessibility: screen reader and keyboard improvements
+
+## Summary
+
+Improvements to support screen reader and keyboard users across the main app surfaces: audio player, generation UI, voice selection, history, voices tab, model management, server tab, and stories.
+
+**Tested with NVDA and Narrator on Windows.**
+
+---
+
+## What changed
+
+### Audio player (after generating audio)
+
+- **Play/Pause, Loop, Mute, Close** – `aria-label` added so each control is announced (e.g. "Play", "Pause", "Loop", "Mute", "Close player").
+- **Playback position slider** – `aria-label="Playback position"` and `aria-valuetext` with current/total time (e.g. "0:30 of 2:15").
+- **Volume** – Wrapped in a labelled group; volume slider has an associated screen-reader-only label and `aria-valuetext` for the level (e.g. "Volume level, 75%").
+
+### Generation UI (text box and voice choice)
+
+- **Generate speech** (submit) and **Fine-tune instructions** (sliders) – Icon buttons now have `aria-label` (and state for fine-tune, e.g. "Fine-tune instructions, on").
+
+### Voice selection (cards on Generate screen)
+
+- Each **voice card** is focusable (`tabIndex={0}`), has `role="button"`, and an `aria-label` (e.g. "Prashant, en. Select as voice for generation.") with `aria-pressed` when selected.
+- **Enter/Space** on the card selects that voice; tab order is card → Export/Edit/Delete.
+
+### History list (generated samples)
+
+- Each **sample row** is focusable with `role="button"` and an `aria-label` (e.g. "Sample from [profile], [duration], [date]. Press Enter to play."); **Enter/Space** plays or restarts.
+- **Transcript textarea** has `aria-label` (e.g. "Transcript for sample from [profile], [duration]") so when you focus on the text area, the sample is announced in context.
+
+### Voices tab (table)
+
+- Each **voice row** is focusable with `role="button"` and an `aria-label` (e.g. "[Name], [language], [N] generations, [N] samples. Press Enter to edit."); **Enter/Space** opens edit (except when focus is in a control).
+- **Actions** dropdown trigger has `aria-label="Actions for [profile name]"`.
+
+### Model management
+
+- Each **model row** is a focusable region (`tabIndex={0}`, `role="group"`) with an `aria-label` (e.g. "[Model name], [status], [size]. Use Tab to reach Download or Delete.").
+- **Download** and **Delete** (and Downloading) buttons have `aria-label` (e.g. "Download [name]", "Delete [name]").
+
+### Server tab (panels)
+
+- **Server Connection**, **Server Status**, and **App Updates** cards are landmarks: `role="region"`, `aria-label`, and `tabIndex={0}` so each panel is focusable and announced (e.g. "Server Connection", "Server Status", "App Updates").
+
+### Stories list
+
+- Each **story row** is a focusable control (`role="button"`, `tabIndex={0}`) with `aria-label` (e.g. "Story [name], [N] items, [date]. Press Enter to select."); **Enter/Space** selects the story. Actions button has `aria-label="Actions for [story name]"`.
+
+### Other controls
+
+- **Story list** – Actions (⋮) button: `aria-label="Actions for [story name]"`.
+- **Story track editor** – Play/Pause, Stop, Split, Duplicate, Delete, Zoom in/out: `aria-label` on all icon buttons.
+- **Voice profile samples** (SampleList, AudioSampleUpload, AudioSampleRecording, AudioSampleSystem) – Play/Pause and Stop: `aria-label` (e.g. "Play sample", "Pause", "Stop playback").
+- **SampleList** mini sample player – Seek slider has `aria-label="Sample playback position"` and `aria-valuetext` for time.
+
+---
+
+## Testing
+
+- **Screen readers:** Tested with **NVDA** and **Narrator** on Windows.
+- **Keyboard:** Tab order and Enter/Space activation verified for focusable rows and buttons.
+
+---
+
+## Tech note
+
+- React + TypeScript; Radix UI primitives; labels added via `aria-label`, `aria-labelledby`, `aria-valuetext`, and `role`/`tabIndex` where needed.
+- No new dependencies.