disable cuda for 0.1.12

Fix dl notification when generating from already cached model

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.4
+current_version = 0.1.12
 commit = True
 tag = True
 tag_name = v{new_version}
@@ -34,6 +34,6 @@ replace = "version": "{new_version}"
 search = "version": "{current_version}"
 replace = "version": "{new_version}"
 
-[bumpversion:file:backend/main.py]
-search = "version": "{current_version}"
-replace = "version": "{new_version}"
+[bumpversion:file:backend/__init__.py]
+search = __version__ = "{current_version}"
+replace = __version__ = "{new_version}"

.github/workflows/release.yml

@@ -4,7 +4,7 @@ on:
   workflow_dispatch:
   push:
     tags:
-      - 'v*'
+      - "v*"
 
 jobs:
   release:
@@ -14,18 +14,22 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - platform: 'macos-latest'
-            args: '--target aarch64-apple-darwin'
-            python-version: '3.12'
-          - platform: 'macos-15-intel'
-            args: '--target x86_64-apple-darwin'
-            python-version: '3.12'
+          - platform: "macos-latest"
+            args: "--target aarch64-apple-darwin"
+            python-version: "3.12"
+            backend: "mlx"
+          - platform: "macos-15-intel"
+            args: "--target x86_64-apple-darwin"
+            python-version: "3.12"
+            backend: "pytorch"
           # - platform: 'ubuntu-22.04'
           #   args: ''
           #   python-version: '3.12'
-          - platform: 'windows-latest'
-            args: ''
-            python-version: '3.12'
+          #   backend: 'pytorch'
+          - platform: "windows-latest"
+            args: ""
+            python-version: "3.12"
+            backend: "pytorch"
 
     runs-on: ${{ matrix.platform }}
 
@@ -49,7 +53,7 @@ jobs:
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
-          cache: 'pip'
+          cache: "pip"
 
       - name: Install Python dependencies
         run: |
@@ -57,6 +61,17 @@ jobs:
           pip install pyinstaller
           pip install -r backend/requirements.txt
 
+      - name: Install MLX dependencies (Apple Silicon only)
+        if: matrix.backend == 'mlx'
+        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: |
@@ -91,7 +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
@@ -127,13 +142,14 @@ jobs:
         with:
           projectPath: tauri
           tagName: v__VERSION__
-          releaseName: 'voicebox v__VERSION__'
+          releaseName: "voicebox v__VERSION__"
           releaseBody: |
             ## What's Changed
             See the assets below to download and install this version.
 
             ### Installation
-            - **macOS**: Download the `.dmg` file
+            - **macOS (Apple Silicon)**: Download the `aarch64.dmg` file - uses MLX for fast native inference
+            - **macOS (Intel)**: Download the `x64.dmg` file - uses PyTorch
             - **Windows**: Download the `.msi` installer
             - **Linux**: Download the `.AppImage` or `.deb` package
 

.npmrc

@@ -0,0 +1,2 @@
+# Force bun usage
+engine-strict=true

CHANGELOG.md

@@ -53,6 +53,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+### Added
+- **Makefile** - Comprehensive development workflow automation with commands for setup, development, building, testing, and code quality checks
+  - Includes Python version detection and compatibility warnings
+  - Self-documenting help system with `make help`
+  - Colored output for better readability
+  - Supports parallel development server execution
+
+### Changed
+- **README** - Added Makefile reference and updated Quick Start with Makefile-based setup instructions alongside manual setup
+
+---
+
+## [Unreleased - Planned]
+
 ### Planned
 - Real-time streaming synthesis
 - Conversation mode with multiple speakers

CONTRIBUTING.md

@@ -32,6 +32,10 @@ Thank you for your interest in contributing to Voicebox! This document provides
 
 ### 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.
+
+**Manual setup (required for Windows):**
+
 1. **Fork and clone the repository**
    ```bash
    git clone https://github.com/YOUR_USERNAME/voicebox.git
@@ -62,37 +66,43 @@ Thank you for your interest in contributing to Voicebox! This document provides
    # Install Python dependencies
    pip install -r requirements.txt
    
+   # Install MLX dependencies (Apple Silicon only - for faster inference)
+   # On Apple Silicon, this enables native Metal acceleration
+   if [[ $(uname -m) == "arm64" ]]; then
+     pip install -r requirements-mlx.txt
+   fi
+   
    # Install Qwen3-TTS (required for voice synthesis)
    pip install git+https://github.com/QwenLM/Qwen3-TTS.git
    ```
 
-4. **Initialize database**
-   ```bash
-   cd backend
-   python -c "from database import init_db; init_db()"
-   ```
-   This creates the SQLite database at `data/voicebox.db`.
+4. **Start development servers**
 
-5. **Start development servers**
-   
-   **Terminal 1: Backend server**
+   Development requires two terminals: one for the Python backend, one for the Tauri app.
+
+   **Terminal 1: Backend server** (start this first)
    ```bash
    cd backend
    source venv/bin/activate  # Activate venv if not already active
    bun run dev:server
-   # Or manually: uvicorn main:app --reload --port 8000
+   # Or manually: uvicorn main:app --reload --port 17493
    ```
-   Backend will be available at `http://localhost:8000`
-   
+   Backend will be available at `http://localhost:17493`
+
    **Terminal 2: Desktop app**
    ```bash
    bun run dev
    ```
    This will:
+   - Create a placeholder sidecar binary (for Tauri compilation)
    - Start Vite dev server on port 5173
    - Launch Tauri window pointing to localhost:5173
+   - Connect to the Python server you started in Terminal 1
    - Enable hot reload
 
+   > **Note:** In dev mode, the app connects to your manually-started Python server.
+   > The bundled server binary is only used in production builds.
+
    **Optional: Web app**
    ```bash
    bun run dev:web
@@ -109,18 +119,36 @@ First-time usage will be slower due to model downloads, but subsequent runs will
 
 ### Building
 
-**Build Python server binary:**
+**Build everything (recommended):**
 ```bash
+bun run build
+```
+This automatically:
+1. Builds the Python server binary (`./scripts/build-server.sh`)
+2. Builds the Tauri desktop app (`cd tauri && bun run tauri build`)
+
+Creates platform-specific installers (`.dmg`, `.msi`, `.AppImage`) in `tauri/src-tauri/target/release/bundle/`.
+
+**Note:** The build process detects your platform and includes the appropriate backend (MLX for Apple Silicon, PyTorch for others).
+
+**Build server binary only:**
+```bash
+bun run build:server
+# or
 ./scripts/build-server.sh
 ```
 Creates platform-specific binary in `tauri/src-tauri/binaries/`
 
-**Build Tauri desktop app:**
+**Building with local Qwen3-TTS development version:**
+
+If you're actively developing or modifying the Qwen3-TTS library, set the `QWEN_TTS_PATH` environment variable to point to your local clone:
+
 ```bash
-cd tauri
-bun run tauri build
+export QWEN_TTS_PATH=~/path/to/your/Qwen3-TTS
+bun run build:server
 ```
-Creates platform-specific installers (`.dmg`, `.msi`, `.AppImage`)
+
+This makes PyInstaller use your local qwen-tts version instead of the pip-installed package. Useful when testing changes to the TTS library before they're published to PyPI or when using an editable install (`pip install -e`).
 
 **Build web app:**
 ```bash
@@ -137,6 +165,26 @@ After starting the backend server:
 ```
 This downloads the OpenAPI schema and generates the TypeScript client in `app/src/lib/api/`
 
+### Convert Assets to Web Formats
+
+To optimize images and videos for the web, run:
+```bash
+bun run convert:assets
+```
+
+This script:
+- Converts PNG → WebP (better compression, same quality)
+- Converts MOV → WebM (VP9 codec, smaller file size)
+- Processes files in `landing/public/` and `docs/public/`
+- **Deletes original files** after successful conversion
+
+**Requirements:** Install `webp` and `ffmpeg`:
+```bash
+brew install webp ffmpeg
+```
+
+> **Note:** Run this before committing new images or videos to keep the repository size small.
+
 ## Development Workflow
 
 ### 1. Create a Branch

Makefile

@@ -0,0 +1,245 @@
+# Voicebox Makefile
+# Unix-only (macOS/Linux). Windows users should use WSL.
+
+SHELL := /bin/bash
+.DEFAULT_GOAL := help
+
+# Directories
+BACKEND_DIR := backend
+TAURI_DIR := tauri
+WEB_DIR := web
+APP_DIR := app
+
+# Python (prefer 3.12, fallback to 3.13, then python3)
+PYTHON := $(shell command -v python3.12 2>/dev/null || command -v python3.13 2>/dev/null || echo python3)
+VENV := $(CURDIR)/$(BACKEND_DIR)/venv
+VENV_BIN := $(VENV)/bin
+PIP := $(VENV_BIN)/pip
+PYTHON_VENV := $(VENV_BIN)/python
+
+# Colors for output
+BLUE := \033[0;34m
+GREEN := \033[0;32m
+YELLOW := \033[0;33m
+NC := \033[0m # No Color
+
+.PHONY: help
+help: ## Show this help message
+	@echo -e "$(BLUE)Voicebox$(NC) - Development Commands"
+	@echo ""
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | \
+		awk 'BEGIN {FS = ":.*?## "}; {printf "  $(GREEN)%-20s$(NC) %s\n", $$1, $$2}'
+
+# =============================================================================
+# SETUP
+# =============================================================================
+
+.PHONY: setup setup-js setup-python setup-rust
+
+setup: setup-js setup-python ## Full project setup (all dependencies)
+	@echo -e "$(GREEN)✓ Setup complete!$(NC)"
+	@echo -e "  Run $(YELLOW)make dev$(NC) to start development servers"
+
+setup-js: ## Install JavaScript dependencies (bun)
+	@echo -e "$(BLUE)Installing JavaScript dependencies...$(NC)"
+	bun install
+
+setup-python: $(VENV)/bin/activate ## Set up Python virtual environment and dependencies
+	@echo -e "$(BLUE)Installing Python dependencies...$(NC)"
+	$(PIP) install --upgrade pip
+	$(PIP) install -r $(BACKEND_DIR)/requirements.txt
+	@if [ "$$(uname -m)" = "arm64" ] && [ "$$(uname)" = "Darwin" ]; then \
+		echo -e "$(BLUE)Detected Apple Silicon - installing MLX dependencies...$(NC)"; \
+		$(PIP) install -r $(BACKEND_DIR)/requirements-mlx.txt; \
+		echo -e "$(GREEN)✓ MLX backend enabled (native Metal acceleration)$(NC)"; \
+	fi
+	$(PIP) install git+https://github.com/QwenLM/Qwen3-TTS.git
+	@echo -e "$(GREEN)✓ Python environment ready$(NC)"
+
+$(VENV)/bin/activate:
+	@echo -e "$(BLUE)Creating Python virtual environment...$(NC)"
+	@PY_MINOR=$$($(PYTHON) -c "import sys; print(sys.version_info[1])"); \
+	if [ "$$PY_MINOR" -gt 13 ]; then \
+		echo -e "$(YELLOW)Warning: Python 3.$$PY_MINOR detected. ML packages may not be compatible.$(NC)"; \
+		echo -e "$(YELLOW)Recommended: Use Python 3.12 or 3.13 (brew install [email protected])$(NC)"; \
+	fi
+	$(PYTHON) -m venv $(VENV)
+
+setup-rust: ## Install Rust toolchain (if not present)
+	@command -v rustc >/dev/null 2>&1 || curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
+
+# =============================================================================
+# DEVELOPMENT
+# =============================================================================
+
+.PHONY: dev dev-backend dev-frontend dev-web kill-dev
+
+dev: ## Start backend + desktop app (parallel)
+	@echo -e "$(BLUE)Starting development servers...$(NC)"
+	@echo -e "$(YELLOW)Note: If Tauri fails, run 'make build-server' first or use separate terminals$(NC)"
+	@trap 'kill 0' EXIT; \
+		$(MAKE) dev-backend & \
+		sleep 2 && $(MAKE) dev-frontend & \
+		wait
+
+dev-backend: ## Start FastAPI backend server
+	@echo -e "$(BLUE)Starting backend server on http://localhost:17493$(NC)"
+	$(VENV_BIN)/uvicorn backend.main:app --reload --port 17493
+
+dev-frontend: ## Start Tauri desktop app
+	@echo -e "$(BLUE)Starting Tauri desktop app...$(NC)"
+	bun run dev
+
+dev-web: ## Start backend + web app (parallel)
+	@echo -e "$(BLUE)Starting web development servers...$(NC)"
+	@trap 'kill 0' EXIT; \
+		$(MAKE) dev-backend & \
+		sleep 2 && cd $(WEB_DIR) && bun run dev & \
+		wait
+
+kill-dev: ## Kill all development processes
+	@echo -e "$(YELLOW)Killing development processes...$(NC)"
+	-pkill -f "uvicorn main:app" 2>/dev/null || true
+	-pkill -f "vite" 2>/dev/null || true
+	@echo -e "$(GREEN)✓ Processes killed$(NC)"
+
+# =============================================================================
+# BUILD
+# =============================================================================
+
+.PHONY: build build-server build-tauri build-web
+
+build: build-server build-tauri ## Build everything (server binary + desktop app)
+	@echo -e "$(GREEN)✓ Build complete!$(NC)"
+
+build-server: ## Build Python server binary
+	@echo -e "$(BLUE)Building server binary...$(NC)"
+	PATH="$(VENV_BIN):$$PATH" ./scripts/build-server.sh
+
+build-tauri: ## Build Tauri desktop app
+	@echo -e "$(BLUE)Building Tauri desktop app...$(NC)"
+	cd $(TAURI_DIR) && bun run tauri build
+
+build-web: ## Build web app
+	@echo -e "$(BLUE)Building web app...$(NC)"
+	cd $(WEB_DIR) && bun run build
+	@echo -e "$(GREEN)✓ Web build output in $(WEB_DIR)/dist/$(NC)"
+
+# =============================================================================
+# DATABASE & API
+# =============================================================================
+
+.PHONY: db-init db-reset generate-api
+
+db-init: $(VENV)/bin/activate ## Initialize SQLite database
+	@echo -e "$(BLUE)Initializing database...$(NC)"
+	cd $(BACKEND_DIR) && $(PYTHON_VENV) -c "from database import init_db; init_db()"
+	@echo -e "$(GREEN)✓ Database created at $(BACKEND_DIR)/data/voicebox.db$(NC)"
+
+db-reset: ## Reset database (delete and reinitialize)
+	@echo -e "$(YELLOW)Resetting database...$(NC)"
+	rm -f $(BACKEND_DIR)/data/voicebox.db
+	$(MAKE) db-init
+
+generate-api: ## Generate TypeScript API client from OpenAPI schema
+	@echo -e "$(BLUE)Generating API client...$(NC)"
+	@echo -e "$(YELLOW)Note: Backend must be running (make dev-backend)$(NC)"
+	./scripts/generate-api.sh
+	@echo -e "$(GREEN)✓ API client generated in $(APP_DIR)/src/lib/api/$(NC)"
+
+# =============================================================================
+# CODE QUALITY
+# =============================================================================
+
+.PHONY: lint format typecheck check
+
+lint: ## Run linter (Biome)
+	@echo -e "$(BLUE)Linting...$(NC)"
+	bun run lint
+
+format: ## Format code (Biome)
+	@echo -e "$(BLUE)Formatting...$(NC)"
+	bun run format
+
+typecheck: ## Run TypeScript type checking
+	@echo -e "$(BLUE)Type checking...$(NC)"
+	bun run tsc --noEmit
+
+check: ## Run all checks (Biome lint + format + type check)
+	@echo -e "$(BLUE)Running all checks...$(NC)"
+	bun run check
+	@echo -e "$(GREEN)✓ All checks passed$(NC)"
+
+# =============================================================================
+# TESTING
+# =============================================================================
+
+.PHONY: test test-backend test-frontend
+
+test: test-backend test-frontend ## Run all tests
+	@echo -e "$(GREEN)✓ All tests passed$(NC)"
+
+test-backend: ## Run Python backend tests (requires pytest)
+	@echo -e "$(BLUE)Running backend tests...$(NC)"
+	@if [ -f "$(VENV_BIN)/pytest" ]; then \
+		cd $(BACKEND_DIR) && $(VENV_BIN)/pytest -v; \
+	else \
+		echo -e "$(YELLOW)pytest not installed. Run: $(PIP) install pytest$(NC)"; \
+		exit 1; \
+	fi
+
+test-frontend: ## Run frontend tests (requires test script in package.json)
+	@echo -e "$(BLUE)Running frontend tests...$(NC)"
+	@if bun run test --help >/dev/null 2>&1; then \
+		bun run test; \
+	else \
+		echo -e "$(YELLOW)No test script configured$(NC)"; \
+		exit 1; \
+	fi
+
+# =============================================================================
+# LOGS & DEBUGGING
+# =============================================================================
+
+.PHONY: logs docs
+
+logs: ## Tail backend logs
+	@echo -e "$(BLUE)Tailing logs (Ctrl+C to stop)...$(NC)"
+	tail -f $(BACKEND_DIR)/logs/*.log 2>/dev/null || echo "No log files found"
+
+docs: ## Open API documentation (backend must be running)
+	@echo -e "$(BLUE)Opening API docs...$(NC)"
+	open http://localhost:17493/docs 2>/dev/null || xdg-open http://localhost:17493/docs
+
+# =============================================================================
+# CLEAN
+# =============================================================================
+
+.PHONY: clean clean-python clean-build clean-all
+
+clean: ## Clean build artifacts
+	@echo -e "$(BLUE)Cleaning build artifacts...$(NC)"
+	rm -rf $(TAURI_DIR)/src-tauri/target/release
+	rm -rf $(WEB_DIR)/dist
+	rm -rf $(APP_DIR)/dist
+	@echo -e "$(GREEN)✓ Build artifacts cleaned$(NC)"
+
+clean-python: ## Clean Python cache and virtual environment
+	@echo -e "$(BLUE)Cleaning Python files...$(NC)"
+	rm -rf $(VENV)
+	find $(BACKEND_DIR) -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
+	find $(BACKEND_DIR) -type f -name "*.pyc" -delete 2>/dev/null || true
+	@echo -e "$(GREEN)✓ Python environment cleaned$(NC)"
+
+clean-build: ## Clean Rust/Tauri build cache
+	@echo -e "$(BLUE)Cleaning Rust build cache...$(NC)"
+	cd $(TAURI_DIR)/src-tauri && cargo clean
+	@echo -e "$(GREEN)✓ Rust cache cleaned$(NC)"
+
+clean-all: clean clean-python clean-build ## Nuclear clean (everything)
+	@echo -e "$(BLUE)Cleaning node_modules...$(NC)"
+	rm -rf node_modules
+	rm -rf $(APP_DIR)/node_modules
+	rm -rf $(TAURI_DIR)/node_modules
+	rm -rf $(WEB_DIR)/node_modules
+	@echo -e "$(GREEN)✓ Full clean complete$(NC)"

README.md

@@ -10,6 +10,21 @@
   All running locally on your machine.
 </p>
 
+<p align="center">
+  <a href="https://github.com/jamiepine/voicebox/releases">
+    <img src="https://img.shields.io/github/downloads/jamiepine/voicebox/total?style=flat&color=blue" alt="Downloads" />
+  </a>
+  <a href="https://github.com/jamiepine/voicebox/releases/latest">
+    <img src="https://img.shields.io/github/v/release/jamiepine/voicebox?style=flat" alt="Release" />
+  </a>
+  <a href="https://github.com/jamiepine/voicebox/stargazers">
+    <img src="https://img.shields.io/github/stars/jamiepine/voicebox?style=flat" alt="Stars" />
+  </a>
+  <a href="https://github.com/jamiepine/voicebox/blob/main/LICENSE">
+    <img src="https://img.shields.io/github/license/jamiepine/voicebox?style=flat" alt="License" />
+  </a>
+</p>
+
 <p align="center">
   <a href="https://voicebox.sh">voicebox.sh</a> •
   <a href="#download">Download</a> •
@@ -22,7 +37,7 @@
 
 <p align="center">
   <a href="https://voicebox.sh">
-    <img src=".github/assets/screenshot.webp" alt="Voicebox App Screenshot" width="800" />
+    <img src="landing/public/assets/app-screenshot-1.webp" alt="Voicebox App Screenshot" width="800" />
   </a>
 </p>
 
@@ -32,17 +47,30 @@
 
 <br/>
 
-## Why Voicebox?
+<p align="center">
+  <img src="landing/public/assets/app-screenshot-2.webp" alt="Voicebox Screenshot 2" width="800" />
+</p>
 
-Voice AI is exploding, but most tools are either cloud-locked, expensive, or a nightmare to set up. Voicebox is different:
+<p align="center">
+  <img src="landing/public/assets/app-screenshot-3.webp" alt="Voicebox Screenshot 3" width="800" />
+</p>
 
-- **100% Local** — Your voice data never leaves your machine
-- **Lightweight** — No bloated Electron, native Tauri performance
-- **Fast** — Near-instant on CUDA, optimized for Apple Silicon
-- **Flexible** — Use the app, integrate the API, or both
-- **Open Source** — No subscriptions, no limits, no lock-in
+<br/>
 
-Built with **Tauri** (Rust), **TypeScript**, **React**, and **Python**. Native performance meets modern DX.
+## 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.
+
+Unlike cloud services that lock your voice data behind subscriptions, Voicebox gives you:
+
+- **Complete privacy** — models and voice data stay on your machine
+- **Professional tools** — multi-track timeline editor, audio trimming, conversation mixing
+- **Model flexibility** — currently powered by Qwen3-TTS, with support for XTTS, Bark, and other models coming soon
+- **API-first** — use the desktop app or integrate voice synthesis into your own projects
+- **Native performance** — built with Tauri (Rust), not Electron
+- **Super fast on Mac** — MLX backend with native Metal acceleration for 4-5x faster inference on Apple Silicon
+
+Download a voice model, clone any voice from a few seconds of audio, and compose multi-voice projects with studio-grade editing tools. No Python install required, no cloud dependency, no limits.
 
 ---
 
@@ -70,11 +98,13 @@ Powered by Alibaba's **Qwen3-TTS** — a breakthrough model that achieves near-p
 - **Instant cloning** — Upload a sample, get a voice profile
 - **High fidelity** — Natural prosody, emotion, and cadence
 - **Multi-language** — English, Chinese, and more coming
+- **Lightning fast on Mac** — MLX backend leverages Apple Silicon's Neural Engine for super fast generation
 
 ### Voice Profile Management
 
 - **Create profiles** from audio files or record directly in-app
 - **Import/Export** profiles to share or backup
+- **Multi-sample support** — combine multiple samples for higher quality cloning
 - **Organize** with descriptions and language tags
 
 ### Speech Generation
@@ -83,9 +113,19 @@ Powered by Alibaba's **Qwen3-TTS** — a breakthrough model that achieves near-p
 - **Batch generation** for long-form content
 - **Smart caching** — regenerate instantly with voice prompt caching
 
+### Stories Editor
+
+Create multi-voice narratives, podcasts, and conversations with a timeline-based editor.
+
+- **Multi-track composition** — arrange multiple voice tracks in a single project
+- **Inline audio editing** — trim and split clips directly in the timeline
+- **Auto-playback** — preview stories with synchronized playhead
+- **Voice mixing** — build conversations with multiple participants
+
 ### Recording & Transcription
 
 - **In-app recording** with waveform visualization
+- **System audio capture** — record desktop audio on macOS and Windows
 - **Automatic transcription** powered by Whisper
 - **Export recordings** in multiple formats
 
@@ -109,17 +149,17 @@ Voicebox exposes a full REST API, so you can integrate voice synthesis into your
 
 ```bash
 # Generate speech
-curl -X POST http://localhost:8000/api/generate \
+curl -X POST http://localhost:8000/generate \
   -H "Content-Type: application/json" \
-  -d '{"text": "Hello world", "profile_id": "abc123"}'
+  -d '{"text": "Hello world", "profile_id": "abc123", "language": "en"}'
 
 # List voice profiles
-curl http://localhost:8000/api/profiles
+curl http://localhost:8000/profiles
 
-# Create a profile from audio
-curl -X POST http://localhost:8000/api/profiles \
-  -F "[email protected]" \
-  -F "name=My Voice"
+# Create a profile
+curl -X POST http://localhost:8000/profiles \
+  -H "Content-Type: application/json" \
+  -d '{"name": "My Voice", "language": "en"}'
 ```
 
 **Use cases:**
@@ -142,8 +182,9 @@ Full API documentation available at `http://localhost:8000/docs` when running.
 | Frontend | React, TypeScript, Tailwind CSS |
 | State | Zustand, React Query |
 | Backend | FastAPI (Python) |
-| Voice Model | Qwen3-TTS |
-| Transcription | Whisper |
+| Voice Model | Qwen3-TTS (PyTorch or MLX) |
+| Transcription | Whisper (PyTorch or MLX) |
+| Inference Engine | MLX (Apple Silicon) / PyTorch (Windows/Linux/Intel) |
 | Database | SQLite |
 | Audio | WaveSurfer.js, librosa |
 
@@ -184,8 +225,26 @@ 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/voicebox-sh/voicebox.git
+cd voicebox
+
+# Setup everything
+make setup
+
+# Start development
+make dev
+```
+
+**Manual setup (all platforms):**
+
 ```bash
 # Clone the repo
 git clone https://github.com/voicebox-sh/voicebox.git
@@ -201,7 +260,11 @@ cd backend && pip install -r requirements.txt && cd ..
 bun run dev
 ```
 
-**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org). CUDA-capable GPU recommended (CPU inference supported but slower).
+**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
+- **Windows/Linux/Intel Mac**: Uses PyTorch backend (CUDA GPU recommended, CPU supported but slower)
 
 ### Project Structure
 

app/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@voicebox/app",
-  "version": "0.1.4",
+  "version": "0.1.12",
   "private": true,
   "type": "module",
   "scripts": {
@@ -13,6 +13,9 @@
     "check": "biome check --write src"
   },
   "dependencies": {
+    "@dnd-kit/core": "^6.3.1",
+    "@dnd-kit/sortable": "^10.0.0",
+    "@dnd-kit/utilities": "^3.2.2",
     "@hookform/resolvers": "^3.9.0",
     "@radix-ui/react-alert-dialog": "^1.1.1",
     "@radix-ui/react-avatar": "^1.1.0",
@@ -30,6 +33,7 @@
     "@radix-ui/react-toast": "^1.2.1",
     "@tanstack/react-query": "^5.0.0",
     "@tanstack/react-query-devtools": "^5.0.0",
+    "@tanstack/react-router": "^1.157.16",
     "@tauri-apps/api": "^2.0.0",
     "@tauri-apps/plugin-dialog": "^2.0.0",
     "@tauri-apps/plugin-fs": "^2.0.0",
@@ -44,6 +48,7 @@
     "react": "^18.3.0",
     "react-dom": "^18.3.0",
     "react-hook-form": "^7.53.0",
+    "react-sound-visualizer": "^1.4.0",
     "tailwind-merge": "^2.5.4",
     "wavesurfer.js": "^7.0.0",
     "zod": "^3.23.8",

app/src/App.tsx

@@ -1,32 +1,15 @@
-import { useEffect, useState } from 'react';
+import { RouterProvider } from '@tanstack/react-router';
+import { useEffect, useRef, useState } from 'react';
 import voiceboxLogo from '@/assets/voicebox-logo.png';
-import { AppFrame } from '@/components/AppFrame/AppFrame';
-import { AudioTab } from '@/components/AudioTab/AudioTab';
-import { MainEditor } from '@/components/MainEditor/MainEditor';
-import { ModelsTab } from '@/components/ModelsTab/ModelsTab';
-import { ServerTab } from '@/components/ServerTab/ServerTab';
-// import { GenerationForm } from '@/components/Generation/GenerationForm';
 import ShinyText from '@/components/ShinyText';
-import { Sidebar } from '@/components/Sidebar';
 import { TitleBarDragRegion } from '@/components/TitleBarDragRegion';
-import { Toaster } from '@/components/ui/toaster';
-import { VoicesTab } from '@/components/VoicesTab/VoicesTab';
+import { useAutoUpdater } from '@/hooks/useAutoUpdater';
 import { TOP_SAFE_AREA_PADDING } from '@/lib/constants/ui';
-import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
-import { MODEL_DISPLAY_NAMES, useRestoreActiveTasks } from '@/lib/hooks/useRestoreActiveTasks';
-import {
-  isMacOS,
-  isTauri,
-  setKeepServerRunning,
-  setupWindowCloseHandler,
-  startServer,
-} from '@/lib/tauri';
 import { cn } from '@/lib/utils/cn';
+import { usePlatform } from '@/platform/PlatformContext';
+import { router } from '@/router';
 import { useServerStore } from '@/stores/serverStore';
 
-// Track if server is starting to prevent duplicate starts
-let serverStarting = false;
-
 const LOADING_MESSAGES = [
   'Warming up tensors...',
   'Calibrating synthesizer engine...',
@@ -51,32 +34,45 @@ const LOADING_MESSAGES = [
 ];
 
 function App() {
-  const [activeTab, setActiveTab] = useState('main');
+  const platform = usePlatform();
   const [serverReady, setServerReady] = useState(false);
   const [loadingMessageIndex, setLoadingMessageIndex] = useState(0);
+  const serverStartingRef = useRef(false);
 
-  // Monitor active downloads/generations and show toasts for them
-  const activeDownloads = useRestoreActiveTasks();
+  // 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 (isTauri()) {
+    if (platform.metadata.isTauri) {
       const keepRunning = useServerStore.getState().keepServerRunningOnClose;
-      setKeepServerRunning(keepRunning).catch((error) => {
+      platform.lifecycle.setKeepServerRunning(keepRunning).catch((error) => {
         console.error('Failed to sync initial setting to Rust:', error);
       });
     }
-  }, []);
+    // Empty dependency array - platform is stable from context, only run once
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.metadata.isTauri, platform.lifecycle]);
+
+  // Setup lifecycle callbacks
+  useEffect(() => {
+    platform.lifecycle.onServerReady = () => {
+      setServerReady(true);
+    };
+    // Empty dependency array - platform is stable from context, only run once
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.lifecycle]);
 
   // Setup window close handler and auto-start server when running in Tauri (production only)
   useEffect(() => {
-    if (!isTauri()) {
+    if (!platform.metadata.isTauri) {
+      setServerReady(true); // Web assumes server is running
       return;
     }
 
     // Setup window close handler to check setting and stop server if needed
     // This works in both dev and prod, but will only stop server if it was started by the app
-    setupWindowCloseHandler().catch((error) => {
+    platform.lifecycle.setupWindowCloseHandler().catch((error) => {
       console.error('Failed to setup window close handler:', error);
     });
 
@@ -92,14 +88,15 @@ function App() {
     }
 
     // Auto-start server in production
-    if (serverStarting) {
+    if (serverStartingRef.current) {
       return;
     }
 
-    serverStarting = true;
+    serverStartingRef.current = true;
     console.log('Production mode: Starting bundled server...');
 
-    startServer(false)
+    platform.lifecycle
+      .startServer(false)
       .then((serverUrl) => {
         console.log('Server is ready at:', serverUrl);
         // Update the server URL in the store with the dynamically assigned port
@@ -111,7 +108,7 @@ function App() {
       })
       .catch((error) => {
         console.error('Failed to auto-start server:', error);
-        serverStarting = false;
+        serverStartingRef.current = false;
         // @ts-expect-error - adding property to window
         window.__voiceboxServerStartedByApp = false;
       });
@@ -120,13 +117,15 @@ function App() {
     // Note: Window close is handled separately in Tauri Rust code
     return () => {
       // Window close event handles server shutdown based on setting
-      serverStarting = false;
+      serverStartingRef.current = false;
     };
-  }, []);
+    // Empty dependency array - platform is stable from context, only run once
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.metadata.isTauri, platform.lifecycle]);
 
   // Cycle through loading messages every 3 seconds
   useEffect(() => {
-    if (!isTauri() || serverReady) {
+    if (!platform.metadata.isTauri || serverReady) {
       return;
     }
 
@@ -135,10 +134,10 @@ function App() {
     }, 3000);
 
     return () => clearInterval(interval);
-  }, [serverReady]);
+  }, [serverReady, platform.metadata.isTauri]);
 
   // Show loading screen while server is starting in Tauri
-  if (isTauri() && !serverReady) {
+  if (platform.metadata.isTauri && !serverReady) {
     return (
       <div
         className={cn(
@@ -172,57 +171,7 @@ function App() {
     );
   }
 
-  return (
-    <AppFrame>
-      <div className="flex flex-1 min-h-0 overflow-hidden">
-        <Sidebar activeTab={activeTab} onTabChange={setActiveTab} isMacOS={isMacOS()} />
-
-        <main className="flex-1 ml-20 overflow-hidden flex flex-col">
-          <div className="container mx-auto px-8 max-w-[1800px] h-full overflow-hidden flex flex-col">
-            {activeTab === 'main' && <MainEditor />}
-            {activeTab === 'voices' && <VoicesTab />}
-            {activeTab === 'audio' && <AudioTab />}
-            {activeTab === 'server' && <ServerTab />}
-            {activeTab === 'models' && <ModelsTab />}
-          </div>
-        </main>
-      </div>
-
-      {/* Show download toasts for any active downloads (from anywhere) */}
-      {activeDownloads.map((download) => {
-        const displayName = MODEL_DISPLAY_NAMES[download.model_name] || download.model_name;
-        return (
-          <DownloadToastRestorer
-            key={download.model_name}
-            modelName={download.model_name}
-            displayName={displayName}
-          />
-        );
-      })}
-
-      <Toaster />
-    </AppFrame>
-  );
-}
-
-/**
- * Component that restores a download toast for a specific model.
- */
-function DownloadToastRestorer({
-  modelName,
-  displayName,
-}: {
-  modelName: string;
-  displayName: string;
-}) {
-  // Use the download toast hook to restore the toast
-  useModelDownloadToast({
-    modelName,
-    displayName,
-    enabled: true,
-  });
-
-  return null;
+  return <RouterProvider router={router} />;
 }
 
 export default App;

app/src/components/AppFrame/AppFrame.tsx

@@ -1,18 +1,35 @@
+import { useRouterState } from '@tanstack/react-router';
 import { TitleBarDragRegion } from '@/components/TitleBarDragRegion';
 import { AudioPlayer } from '@/components/AudioPlayer/AudioPlayer';
+import { StoryTrackEditor } from '@/components/StoriesTab/StoryTrackEditor';
 import { TOP_SAFE_AREA_PADDING } from '@/lib/constants/ui';
 import { cn } from '@/lib/utils/cn';
+import { useStoryStore } from '@/stores/storyStore';
+import { useStory } from '@/lib/hooks/useStories';
 
 interface AppFrameProps {
   children: React.ReactNode;
 }
 
 export function AppFrame({ children }: AppFrameProps) {
+  const routerState = useRouterState();
+  const isStoriesRoute = routerState.location.pathname === '/stories';
+  
+  const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
+  const { data: story } = useStory(selectedStoryId);
+  
+  // Show track editor when on stories route with a selected story that has items
+  const showTrackEditor = isStoriesRoute && selectedStoryId && story && story.items.length > 0;
+
   return (
     <div className={cn('h-screen bg-background flex flex-col overflow-hidden', TOP_SAFE_AREA_PADDING)}>
       <TitleBarDragRegion />
       {children}
-      <AudioPlayer />
+      {showTrackEditor ? (
+        <StoryTrackEditor storyId={story.id} items={story.items} />
+      ) : (
+        <AudioPlayer />
+      )}
     </div>
   );
 }

app/src/components/AudioPlayer/AudioPlayer.tsx

@@ -1,16 +1,17 @@
 import { useQuery } from '@tanstack/react-query';
-import { invoke } from '@tauri-apps/api/core';
 import { Pause, Play, Repeat, Volume2, VolumeX, X } from 'lucide-react';
 import { useEffect, useMemo, useRef, useState } from 'react';
 import WaveSurfer from 'wavesurfer.js';
 import { Button } from '@/components/ui/button';
 import { Slider } from '@/components/ui/slider';
 import { apiClient } from '@/lib/api/client';
-import { isTauri } from '@/lib/tauri';
 import { formatAudioDuration } from '@/lib/utils/audio';
+import { debug } from '@/lib/utils/debug';
 import { usePlayerStore } from '@/stores/playerStore';
+import { usePlatform } from '@/platform/PlatformContext';
 
 export function AudioPlayer() {
+  const platform = usePlatform();
   const {
     audioUrl,
     audioId,
@@ -38,7 +39,7 @@ export function AudioPlayer() {
       if (!profileId) return { channel_ids: [] };
       return apiClient.getProfileChannels(profileId);
     },
-    enabled: !!profileId && isTauri(),
+    enabled: !!profileId && platform.metadata.isTauri,
   });
 
   const { data: channels } = useQuery({
@@ -49,28 +50,17 @@ export function AudioPlayer() {
 
   // Determine if we should use native playback
   const useNativePlayback = useMemo(() => {
-    console.log('useNativePlayback memo:', {
-      isTauri: isTauri(),
-      profileId,
-      profileChannels,
-      channels,
-    });
-
-    if (!isTauri() || !profileChannels || !channels) {
-      console.log('useNativePlayback: false - missing requirements');
+    if (!platform.metadata.isTauri || !profileChannels || !channels) {
       return false;
     }
 
     const assignedChannels = channels.filter((ch) => profileChannels.channel_ids.includes(ch.id));
 
-    console.log('Assigned channels:', assignedChannels);
-
     // Use native playback if any assigned channel has non-default devices
     const shouldUseNative = assignedChannels.some(
       (ch) => ch.device_ids.length > 0 && !ch.is_default,
     );
 
-    console.log('useNativePlayback result:', shouldUseNative);
     return shouldUseNative;
   }, [profileChannels, channels, profileId]);
 
@@ -91,11 +81,11 @@ export function AudioPlayer() {
     }
 
     if (wavesurferRef.current) {
-      console.log('WaveSurfer already initialized, skipping');
+      debug.log('WaveSurfer already initialized, skipping');
       return;
     }
 
-    console.log('Creating NEW WaveSurfer instance');
+    debug.log('Creating NEW WaveSurfer instance');
 
     // Wait for container to be properly rendered
     const initWaveSurfer = () => {
@@ -121,7 +111,7 @@ export function AudioPlayer() {
         return;
       }
 
-      console.log('Initializing WaveSurfer...', {
+      debug.log('Initializing WaveSurfer...', {
         container,
         width: rect.width,
         height: rect.height,
@@ -154,9 +144,9 @@ export function AudioPlayer() {
         });
 
         wavesurferRef.current = wavesurfer;
-        console.log('WaveSurfer created successfully');
+        debug.log('WaveSurfer created successfully');
       } catch (error) {
-        console.error('Failed to create WaveSurfer:', error);
+        debug.error('Failed to create WaveSurfer:', error);
         setError(
           `Failed to initialize waveform: ${error instanceof Error ? error.message : String(error)}`,
         );
@@ -178,8 +168,8 @@ export function AudioPlayer() {
         loadingRef.current = false;
         setIsLoading(false);
         setError(null);
-        console.log('Audio ready, duration:', dur);
-        console.log('Waveform should be visible now');
+        debug.log('Audio ready, duration:', dur);
+        debug.log('Waveform should be visible now');
 
         // Ensure volume is set
         const currentVolume = usePlayerStore.getState().volume;
@@ -191,7 +181,7 @@ export function AudioPlayer() {
         if (mediaElement && !isUsingNativePlaybackRef.current) {
           mediaElement.volume = currentVolume;
           mediaElement.muted = false;
-          console.log('Audio element volume:', mediaElement.volume, 'muted:', mediaElement.muted);
+          debug.log('Audio element volume:', mediaElement.volume, 'muted:', mediaElement.muted);
         }
 
         // Auto-play when ready - check if we should use native playback
@@ -199,28 +189,28 @@ export function AudioPlayer() {
         const currentAudioUrl = usePlayerStore.getState().audioUrl;
         const currentProfileId = usePlayerStore.getState().profileId;
 
-        console.log('Auto-play check - capturing runtime values...');
+        debug.log('Auto-play check - capturing runtime values...');
 
         // Fetch profile channels at runtime (not using captured value)
         let runtimeProfileChannels = null;
         let runtimeChannels = null;
 
-        if (isTauri() && currentProfileId) {
+        if (platform.metadata.isTauri && currentProfileId) {
           try {
             runtimeProfileChannels = await apiClient.getProfileChannels(currentProfileId);
-            console.log('Runtime profileChannels:', runtimeProfileChannels);
+            debug.log('Runtime profileChannels:', runtimeProfileChannels);
 
             if (runtimeProfileChannels && runtimeProfileChannels.channel_ids.length > 0) {
               runtimeChannels = await apiClient.listChannels();
-              console.log('Runtime channels:', runtimeChannels);
+              debug.log('Runtime channels:', runtimeChannels);
             }
           } catch (error) {
-            console.error('Failed to fetch runtime channel data:', error);
+            debug.error('Failed to fetch runtime channel data:', error);
           }
         }
 
-        console.log('Auto-play check:', {
-          isTauri: isTauri(),
+        debug.log('Auto-play check:', {
+          isTauri: platform.metadata.isTauri,
           currentAudioUrl,
           currentProfileId,
           hasProfileChannels: !!runtimeProfileChannels,
@@ -228,21 +218,21 @@ export function AudioPlayer() {
         });
 
         if (
-          isTauri() &&
+          platform.metadata.isTauri &&
           currentAudioUrl &&
           currentProfileId &&
           runtimeProfileChannels &&
           runtimeChannels
         ) {
-          console.log('Attempting native audio playback...');
+          debug.log('Attempting native audio playback...');
 
           // Stop any existing native playback first
           if (isUsingNativePlaybackRef.current) {
             try {
-              await invoke('stop_audio_playback');
-              console.log('Stopped existing native playback before starting new one');
+              platform.audio.stopPlayback();
+              debug.log('Stopped existing native playback before starting new one');
             } catch (error) {
-              console.error('Failed to stop existing playback:', error);
+              debug.error('Failed to stop existing playback:', error);
             }
           }
 
@@ -251,16 +241,16 @@ export function AudioPlayer() {
             const assignedChannels = runtimeChannels.filter((ch: any) =>
               runtimeProfileChannels.channel_ids.includes(ch.id),
             );
-            console.log('Assigned channels for playback:', assignedChannels);
+            debug.log('Assigned channels for playback:', assignedChannels);
 
             // Check if any assigned channel has non-default devices
             const shouldUseNative = assignedChannels.some(
               (ch: any) => ch.device_ids.length > 0 && !ch.is_default,
             );
-            console.log('Should use native playback:', shouldUseNative);
+            debug.log('Should use native playback:', shouldUseNative);
 
             if (!shouldUseNative) {
-              console.log('No custom devices assigned, falling back to WaveSurfer');
+              debug.log('No custom devices assigned, falling back to WaveSurfer');
               // Reset native playback flag and unmute WaveSurfer
               isUsingNativePlaybackRef.current = false;
               const mediaElement = wavesurfer.getMediaElement();
@@ -268,7 +258,7 @@ export function AudioPlayer() {
                 const currentVolume = usePlayerStore.getState().volume;
                 mediaElement.volume = currentVolume;
                 mediaElement.muted = false;
-                console.log(
+                debug.log(
                   'WaveSurfer unmuted for normal playback - volume:',
                   mediaElement.volume,
                   'muted:',
@@ -277,23 +267,20 @@ export function AudioPlayer() {
               }
             } else {
               const deviceIds = assignedChannels.flatMap((ch: any) => ch.device_ids);
-              console.log('Device IDs to play to:', deviceIds);
+              debug.log('Device IDs to play to:', deviceIds);
 
               if (deviceIds.length > 0) {
-                console.log('Fetching audio data from:', currentAudioUrl);
+                debug.log('Fetching audio data from:', currentAudioUrl);
                 // Fetch audio data
                 const response = await fetch(currentAudioUrl);
                 const audioData = new Uint8Array(await response.arrayBuffer());
-                console.log('Audio data size:', audioData.length);
+                debug.log('Audio data size:', audioData.length);
 
                 // Play via native audio
-                console.log('Invoking play_audio_to_devices...');
+                debug.log('Invoking play_audio_to_devices...');
                 try {
-                  const result = await invoke('play_audio_to_devices', {
-                    audioData: Array.from(audioData),
-                    deviceIds: deviceIds,
-                  });
-                  console.log('play_audio_to_devices completed successfully, result:', result);
+                  await platform.audio.playToDevices(audioData, deviceIds);
+                  debug.log('play_audio_to_devices completed successfully');
 
                   // Mark that we're using native playback
                   isUsingNativePlaybackRef.current = true;
@@ -304,7 +291,7 @@ export function AudioPlayer() {
                   if (mediaElement) {
                     mediaElement.volume = 0;
                     mediaElement.muted = true;
-                    console.log(
+                    debug.log(
                       'WaveSurfer muted for native playback - volume:',
                       mediaElement.volume,
                       'muted:',
@@ -314,22 +301,22 @@ export function AudioPlayer() {
 
                   // Start WaveSurfer playback for visualization (muted)
                   wavesurfer.play().catch((error) => {
-                    console.error('Failed to start WaveSurfer visualization:', error);
+                    debug.error('Failed to start WaveSurfer visualization:', error);
                   });
 
                   setIsPlaying(true);
-                  console.log('Auto-playing via native audio routing - SUCCESS');
+                  debug.log('Auto-playing via native audio routing - SUCCESS');
                   return;
                 } catch (invokeError) {
-                  console.error('play_audio_to_devices invoke failed:', invokeError);
+                  debug.error('play_audio_to_devices invoke failed:', invokeError);
                   throw invokeError;
                 }
               } else {
-                console.log('No device IDs found, falling back to WaveSurfer');
+                debug.log('No device IDs found, falling back to WaveSurfer');
               }
             }
           } catch (error) {
-            console.error(
+            debug.error(
               'Native playback failed during auto-play, falling back to WaveSurfer:',
               error,
             );
@@ -340,7 +327,7 @@ export function AudioPlayer() {
               const currentVolume = usePlayerStore.getState().volume;
               mediaElement.volume = currentVolume;
               mediaElement.muted = false;
-              console.log(
+              debug.log(
                 'WaveSurfer unmuted after native playback failure - volume:',
                 mediaElement.volume,
                 'muted:',
@@ -350,7 +337,7 @@ export function AudioPlayer() {
             // Fall through to WaveSurfer playback
           }
         } else {
-          console.log('Not using native playback, using WaveSurfer');
+          debug.log('Not using native playback, using WaveSurfer');
           // Reset native playback flag and unmute WaveSurfer
           isUsingNativePlaybackRef.current = false;
           const mediaElement = wavesurfer.getMediaElement();
@@ -358,7 +345,7 @@ export function AudioPlayer() {
             const currentVolume = usePlayerStore.getState().volume;
             mediaElement.volume = currentVolume;
             mediaElement.muted = false;
-            console.log(
+            debug.log(
               'WaveSurfer unmuted for normal playback - volume:',
               mediaElement.volume,
               'muted:',
@@ -367,14 +354,22 @@ export function AudioPlayer() {
           }
         }
 
-        // Standard WaveSurfer auto-play
-        // Use a small delay to ensure audio element is fully ready
-        setTimeout(() => {
-          wavesurfer.play().catch((error) => {
-            console.error('Failed to autoplay:', error);
-            // Don't show error for autoplay failures (browser restrictions)
-          });
-        }, 100);
+        // Only auto-play if shouldAutoPlay flag is set (user explicitly clicked to play)
+        const shouldAutoPlayNow = usePlayerStore.getState().shouldAutoPlay;
+        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) => {
+              debug.error('Failed to autoplay:', error);
+              // Don't show error for autoplay failures (browser restrictions)
+            });
+          }, 100);
+        } else {
+          debug.log('Skipping auto-play - shouldAutoPlay is false');
+        }
       });
 
       // Handle play/pause
@@ -388,13 +383,13 @@ export function AudioPlayer() {
           if (isUsingNativePlaybackRef.current) {
             mediaElement.volume = 0;
             mediaElement.muted = true;
-            console.log('Playing (native mode) - WaveSurfer muted for visualization only');
+            debug.log('Playing (native mode) - WaveSurfer muted for visualization only');
           } else {
             // Ensure WaveSurfer is unmuted for normal playback
             const currentVolume = usePlayerStore.getState().volume;
             mediaElement.volume = currentVolume;
             mediaElement.muted = false;
-            console.log(
+            debug.log(
               'Playing (normal mode) - volume:',
               mediaElement.volume,
               'muted:',
@@ -412,12 +407,17 @@ export function AudioPlayer() {
           wavesurfer.play();
         } else {
           setIsPlaying(false);
+          // Trigger finish callback if set
+          const onFinish = usePlayerStore.getState().onFinish;
+          if (onFinish) {
+            onFinish();
+          }
         }
       });
 
       // Handle errors
       wavesurfer.on('error', (error) => {
-        console.error('WaveSurfer error:', error);
+        debug.error('WaveSurfer error:', error);
         setIsLoading(false);
         setError(`Audio error: ${error instanceof Error ? error.message : String(error)}`);
       });
@@ -432,7 +432,7 @@ export function AudioPlayer() {
 
       // Load audio immediately if audioUrl is already set
       if (audioUrl) {
-        console.log('WaveSurfer ready, loading audio:', audioUrl);
+        debug.log('WaveSurfer ready, loading audio:', audioUrl);
         loadingRef.current = true;
         setIsLoading(true);
         // Stop any current playback before loading new audio
@@ -442,11 +442,11 @@ export function AudioPlayer() {
         wavesurfer
           .load(audioUrl)
           .then(() => {
-            console.log('Audio loaded into WaveSurfer');
+            debug.log('Audio loaded into WaveSurfer');
             loadingRef.current = false;
           })
           .catch((error) => {
-            console.error('Failed to load audio into WaveSurfer:', error);
+            debug.error('Failed to load audio into WaveSurfer:', error);
             loadingRef.current = false;
             setIsLoading(false);
             setError(
@@ -471,12 +471,12 @@ export function AudioPlayer() {
     });
 
     return () => {
-      console.log('Cleaning up WaveSurfer initialization effect');
+      debug.log('Cleaning up WaveSurfer initialization effect');
       if (rafId1) cancelAnimationFrame(rafId1);
       if (rafId2) cancelAnimationFrame(rafId2);
       if (timeoutId) clearTimeout(timeoutId);
       if (wavesurferRef.current) {
-        console.log('Destroying WaveSurfer instance');
+        debug.log('Destroying WaveSurfer instance');
         try {
           const mediaElement = wavesurferRef.current.getMediaElement();
           if (mediaElement) {
@@ -485,7 +485,7 @@ export function AudioPlayer() {
           }
           wavesurferRef.current.destroy();
         } catch (error) {
-          console.error('Error destroying WaveSurfer:', error);
+          debug.error('Error destroying WaveSurfer:', error);
         }
         wavesurferRef.current = null;
       }
@@ -513,15 +513,13 @@ export function AudioPlayer() {
     }
 
     // Stop native playback if it was active
-    if (isUsingNativePlaybackRef.current && isTauri()) {
-      (async () => {
-        try {
-          await invoke('stop_audio_playback');
-          console.log('Stopped native audio playback');
-        } catch (error) {
-          console.error('Failed to stop native playback:', error);
-        }
-      })();
+    if (isUsingNativePlaybackRef.current && platform.metadata.isTauri) {
+      try {
+        platform.audio.stopPlayback();
+        debug.log('Stopped native audio playback');
+      } catch (error) {
+        debug.error('Failed to stop native playback:', error);
+      }
     }
 
     // Reset native playback flag when loading new audio
@@ -537,30 +535,30 @@ export function AudioPlayer() {
 
     // CRITICAL: Force stop any current playback and cancel any pending loads
     // This must happen BEFORE any early returns
-    console.log('Audio URL changed to:', audioUrl);
+    debug.log('Audio URL changed to:', audioUrl);
 
     // COMPLETELY stop and destroy the current audio
     try {
       // First pause if playing
       if (wavesurfer.isPlaying()) {
-        console.log('Pausing current playback');
+        debug.log('Pausing current playback');
         wavesurfer.pause();
       }
 
       // Stop the media element explicitly
       const mediaElement = wavesurfer.getMediaElement();
       if (mediaElement) {
-        console.log('Stopping media element');
+        debug.log('Stopping media element');
         mediaElement.pause();
         mediaElement.currentTime = 0;
         mediaElement.src = '';
       }
 
       // Use empty() to completely destroy the waveform and media element
-      console.log('Calling wavesurfer.empty() to destroy audio');
+      debug.log('Calling wavesurfer.empty() to destroy audio');
       wavesurfer.empty();
     } catch (error) {
-      console.error('Error stopping previous audio:', error);
+      debug.error('Error stopping previous audio:', error);
       // Continue anyway to load new audio
     }
 
@@ -575,16 +573,16 @@ export function AudioPlayer() {
     setDuration(0);
 
     // Load new audio
-    console.log('Starting new audio load for:', audioUrl);
+    debug.log('Starting new audio load for:', audioUrl);
     wavesurfer
       .load(audioUrl)
       .then(() => {
-        console.log('Audio load promise resolved');
+        debug.log('Audio load promise resolved');
         // Don't set loading to false here - wait for 'ready' event
       })
       .catch((error) => {
-        console.error('Failed to load audio:', error);
-        console.error('Audio URL:', audioUrl);
+        debug.error('Failed to load audio:', error);
+        debug.error('Audio URL:', audioUrl);
         loadingRef.current = false;
         setIsLoading(false);
         setError(`Failed to load audio: ${error instanceof Error ? error.message : String(error)}`);
@@ -599,7 +597,7 @@ export function AudioPlayer() {
     if (isPlaying && wavesurferRef.current.isPlaying() === false) {
       // Only auto-play if audio is ready
       wavesurferRef.current.play().catch((error) => {
-        console.error('Failed to play:', error);
+        debug.error('Failed to play:', error);
         setIsPlaying(false);
         setError(`Playback error: ${error instanceof Error ? error.message : String(error)}`);
       });
@@ -619,11 +617,11 @@ export function AudioPlayer() {
         if (isUsingNativePlaybackRef.current) {
           mediaElement.volume = 0;
           mediaElement.muted = true;
-          console.log('Volume sync: Using native playback, keeping WaveSurfer muted');
+          debug.log('Volume sync: Using native playback, keeping WaveSurfer muted');
         } else {
           mediaElement.volume = volume;
           mediaElement.muted = volume === 0;
-          console.log('Volume synced:', volume, 'muted:', mediaElement.muted);
+          debug.log('Volume synced:', volume, 'muted:', mediaElement.muted);
         }
       }
     }
@@ -651,10 +649,10 @@ export function AudioPlayer() {
     }
 
     // Reset to beginning and play
-    console.log('Restarting current audio from beginning');
+    debug.log('Restarting current audio from beginning');
     wavesurfer.seekTo(0);
     wavesurfer.play().catch((error) => {
-      console.error('Failed to play after restart:', error);
+      debug.error('Failed to play after restart:', error);
       setIsPlaying(false);
       setError(`Playback error: ${error instanceof Error ? error.message : String(error)}`);
     });
@@ -663,19 +661,42 @@ export function AudioPlayer() {
     clearRestartFlag();
   }, [shouldRestart, duration, setIsPlaying, clearRestartFlag]);
 
+  // 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) {
+      return;
+    }
+
+    // Auto-play the newly loaded audio
+    debug.log('Auto-playing next track in story mode');
+    wavesurfer.seekTo(0);
+    wavesurfer.play().catch((error) => {
+      debug.error('Failed to auto-play:', error);
+      setIsPlaying(false);
+      setError(`Playback error: ${error instanceof Error ? error.message : String(error)}`);
+    });
+
+    // Clear the auto-play flag
+    clearAutoPlayFlag();
+  }, [shouldAutoPlay, duration, setIsPlaying, clearAutoPlayFlag]);
+
   // Handle loop - WaveSurfer handles this via the 'finish' event
 
   const handlePlayPause = async () => {
     // Standard WaveSurfer playback (works for both normal and native playback modes)
     // When using native playback, WaveSurfer is muted but still controls visualization
     if (!wavesurferRef.current) {
-      console.error('WaveSurfer not initialized');
+      debug.error('WaveSurfer not initialized');
       return;
     }
 
     // Check if audio is loaded
     if (duration === 0 && !isLoading) {
-      console.error('Audio not loaded yet');
+      debug.error('Audio not loaded yet');
       setError('Audio not loaded. Please wait...');
       return;
     }
@@ -685,10 +706,10 @@ export function AudioPlayer() {
       if (isPlaying) {
         // Pause: stop native playback and pause WaveSurfer visualization
         try {
-          await invoke('stop_audio_playback');
-          console.log('Stopped native audio playback');
+          platform.audio.stopPlayback();
+          debug.log('Stopped native audio playback');
         } catch (error) {
-          console.error('Failed to stop native playback:', error);
+          debug.error('Failed to stop native playback:', error);
         }
         wavesurferRef.current.pause();
         return;
@@ -698,10 +719,10 @@ export function AudioPlayer() {
       try {
         // Stop any existing native playback first
         try {
-          await invoke('stop_audio_playback');
+          platform.audio.stopPlayback();
         } catch (_error) {
           // Ignore errors when stopping (might not be playing)
-          console.log('No existing playback to stop');
+          debug.log('No existing playback to stop');
         }
 
         // Collect all device IDs from assigned channels
@@ -716,10 +737,7 @@ export function AudioPlayer() {
           const audioData = new Uint8Array(await response.arrayBuffer());
 
           // Play via native audio
-          await invoke('play_audio_to_devices', {
-            audioData: Array.from(audioData),
-            deviceIds: deviceIds,
-          });
+          await platform.audio.playToDevices(audioData, deviceIds);
 
           // Mark that we're using native playback
           isUsingNativePlaybackRef.current = true;
@@ -733,7 +751,7 @@ export function AudioPlayer() {
 
           // Start WaveSurfer for visualization (muted)
           wavesurferRef.current.play().catch((error) => {
-            console.error('Failed to start WaveSurfer visualization:', error);
+            debug.error('Failed to start WaveSurfer visualization:', error);
             setIsPlaying(false);
             setError(`Playback error: ${error instanceof Error ? error.message : String(error)}`);
           });
@@ -741,7 +759,7 @@ export function AudioPlayer() {
           return;
         }
       } catch (error) {
-        console.error('Native playback failed, falling back to WaveSurfer:', error);
+        debug.error('Native playback failed, falling back to WaveSurfer:', error);
         // Fall through to WaveSurfer playback
         isUsingNativePlaybackRef.current = false;
       }
@@ -761,7 +779,7 @@ export function AudioPlayer() {
       }
 
       wavesurferRef.current.play().catch((error) => {
-        console.error('Failed to play:', error);
+        debug.error('Failed to play:', error);
         setIsPlaying(false);
         setError(`Playback error: ${error instanceof Error ? error.message : String(error)}`);
       });
@@ -780,10 +798,12 @@ export function AudioPlayer() {
 
   const handleClose = () => {
     // Stop any native playback
-    if (isUsingNativePlaybackRef.current && isTauri()) {
-      invoke('stop_audio_playback').catch((error) => {
-        console.error('Failed to stop native playback:', error);
-      });
+    if (isUsingNativePlaybackRef.current && platform.metadata.isTauri) {
+      try {
+        platform.audio.stopPlayback();
+      } catch (error) {
+        debug.error('Failed to stop native playback:', error);
+      }
     }
     // Stop WaveSurfer
     if (wavesurferRef.current) {

app/src/components/AudioTab/AudioTab.tsx

@@ -1,5 +1,4 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
-import { invoke } from '@tauri-apps/api/core';
 import { Check, CheckCircle2, Edit, Plus, Speaker, Trash2 } from 'lucide-react';
 import { useState } from 'react';
 import { Badge } from '@/components/ui/badge';
@@ -23,9 +22,9 @@ import {
 } from '@/components/ui/select';
 import { apiClient } from '@/lib/api/client';
 import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
-import { isTauri } from '@/lib/tauri';
 import { cn } from '@/lib/utils/cn';
 import { usePlayerStore } from '@/stores/playerStore';
+import { usePlatform } from '@/platform/PlatformContext';
 
 interface AudioDevice {
   id: string;
@@ -34,6 +33,7 @@ interface AudioDevice {
 }
 
 export function AudioTab() {
+  const platform = usePlatform();
   const [createDialogOpen, setCreateDialogOpen] = useState(false);
   const [editingChannel, setEditingChannel] = useState<string | null>(null);
   const [selectedChannelId, setSelectedChannelId] = useState<string | null>(null);
@@ -49,18 +49,17 @@ export function AudioTab() {
   const { data: devices, isLoading: devicesLoading } = useQuery({
     queryKey: ['audio-devices'],
     queryFn: async () => {
-      if (!isTauri()) {
+      if (!platform.metadata.isTauri) {
         return [];
       }
       try {
-        const result = await invoke<AudioDevice[]>('list_audio_output_devices');
-        return result;
+        return await platform.audio.listOutputDevices();
       } catch (error) {
         console.error('Failed to list audio devices:', error);
         return [];
       }
     },
-    enabled: isTauri(),
+    enabled: platform.metadata.isTauri,
   });
 
   const { data: profiles } = useQuery({
@@ -342,7 +341,7 @@ 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">
-                {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

@@ -1,9 +1,7 @@
-import { zodResolver } from '@hookform/resolvers/zod';
+import { useMatchRoute } from '@tanstack/react-router';
 import { AnimatePresence, motion } from 'framer-motion';
-import { Loader2, Sparkles } from 'lucide-react';
+import { Loader2, MessageSquare, Sparkles } from 'lucide-react';
 import { useEffect, useRef, useState } from 'react';
-import { useForm } from 'react-hook-form';
-import * as z from 'zod';
 import { Button } from '@/components/ui/button';
 import { Form, FormControl, FormField, FormItem, FormMessage } from '@/components/ui/form';
 import {
@@ -15,51 +13,65 @@ import {
 } from '@/components/ui/select';
 import { Textarea } from '@/components/ui/textarea';
 import { useToast } from '@/components/ui/use-toast';
-import { apiClient } from '@/lib/api/client';
-import { LANGUAGE_CODES, LANGUAGE_OPTIONS, type LanguageCode } from '@/lib/constants/languages';
-import { useGeneration } from '@/lib/hooks/useGeneration';
-import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
-import { useProfile } from '@/lib/hooks/useProfiles';
-import { useGenerationStore } from '@/stores/generationStore';
-import { usePlayerStore } from '@/stores/playerStore';
+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 { cn } from '@/lib/utils/cn';
+import { useStoryStore } from '@/stores/storyStore';
 import { useUIStore } from '@/stores/uiStore';
 
-const generationSchema = z.object({
-  text: z.string().min(1, 'Text is required').max(5000),
-  language: z.enum(LANGUAGE_CODES as [LanguageCode, ...LanguageCode[]]),
-  modelSize: z.enum(['1.7B', '0.6B']).optional(),
-});
-
-type GenerationFormValues = z.infer<typeof generationSchema>;
-
 interface FloatingGenerateBoxProps {
-  isPlayerOpen: boolean;
+  isPlayerOpen?: boolean;
+  showVoiceSelector?: boolean;
 }
 
-export function FloatingGenerateBox({ isPlayerOpen }: FloatingGenerateBoxProps) {
+export function FloatingGenerateBox({
+  isPlayerOpen = false,
+  showVoiceSelector = false,
+}: FloatingGenerateBoxProps) {
   const selectedProfileId = useUIStore((state) => state.selectedProfileId);
+  const setSelectedProfileId = useUIStore((state) => state.setSelectedProfileId);
   const { data: selectedProfile } = useProfile(selectedProfileId || '');
-  const generation = useGeneration();
-  const { toast } = useToast();
-  const setAudio = usePlayerStore((state) => state.setAudio);
-  const setIsGenerating = useGenerationStore((state) => state.setIsGenerating);
-  const [downloadingModelName, setDownloadingModelName] = useState<string | null>(null);
-  const [downloadingDisplayName, setDownloadingDisplayName] = useState<string | null>(null);
+  const { data: profiles } = useProfiles();
   const [isExpanded, setIsExpanded] = useState(false);
+  const [isInstructMode, setIsInstructMode] = useState(false);
   const containerRef = useRef<HTMLDivElement>(null);
+  const textareaRef = useRef<HTMLTextAreaElement | null>(null);
+  const matchRoute = useMatchRoute();
+  const isStoriesRoute = matchRoute({ to: '/stories' });
+  const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
+  const trackEditorHeight = useStoryStore((state) => state.trackEditorHeight);
+  const { data: currentStory } = useStory(selectedStoryId);
+  const addStoryItem = useAddStoryItem();
+  const { toast } = useToast();
 
-  useModelDownloadToast({
-    modelName: downloadingModelName || '',
-    displayName: downloadingDisplayName || '',
-    enabled: !!downloadingModelName,
-  });
+  // Calculate if track editor is visible (on stories route with items)
+  const hasTrackEditor = isStoriesRoute && currentStory && currentStory.items.length > 0;
 
-  const form = useForm<GenerationFormValues>({
-    resolver: zodResolver(generationSchema),
-    defaultValues: {
-      text: '',
-      language: 'en',
-      modelSize: '1.7B',
+  const { form, handleSubmit, isPending } = useGenerationForm({
+    onSuccess: async (generationId) => {
+      setIsExpanded(false);
+      // If on stories route and a story is selected, add generation to story
+      if (isStoriesRoute && selectedStoryId && generationId) {
+        try {
+          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',
+          });
+        }
+      }
     },
   });
 
@@ -93,70 +105,85 @@ export function FloatingGenerateBox({ isPlayerOpen }: FloatingGenerateBoxProps)
     };
   }, [isExpanded]);
 
-  async function onSubmit(data: GenerationFormValues) {
-    if (!selectedProfileId) {
-      toast({
-        title: 'No profile selected',
-        description: 'Please select a voice profile from the cards above.',
-        variant: 'destructive',
-      });
-      return;
+  // Set first voice as default if none selected
+  useEffect(() => {
+    if (!selectedProfileId && profiles && profiles.length > 0) {
+      setSelectedProfileId(profiles[0].id);
     }
+  }, [selectedProfileId, profiles, setSelectedProfileId]);
 
-    try {
-      setIsGenerating(true);
-
-      const modelName = `qwen-tts-${data.modelSize}`;
-      const displayName = data.modelSize === '1.7B' ? 'Qwen TTS 1.7B' : 'Qwen TTS 0.6B';
-
-      try {
-        const modelStatus = await apiClient.getModelStatus();
-        const model = modelStatus.models.find((m) => m.model_name === modelName);
-
-        if (model && !model.downloaded) {
-          setDownloadingModelName(modelName);
-          setDownloadingDisplayName(displayName);
+  // Auto-resize textarea based on content (only when expanded)
+  useEffect(() => {
+    if (!isExpanded) {
+      // Reset textarea height after collapse animation completes
+      const timeoutId = setTimeout(() => {
+        const textarea = textareaRef.current;
+        if (textarea) {
+          textarea.style.height = '32px';
+          textarea.style.overflowY = 'hidden';
         }
-      } catch (error) {
-        console.error('Failed to check model status:', error);
-      }
-
-      const result = await generation.mutateAsync({
-        profile_id: selectedProfileId,
-        text: data.text,
-        language: data.language,
-        model_size: data.modelSize,
-      });
-
-      toast({
-        title: 'Generation complete!',
-        description: `Audio generated (${result.duration.toFixed(2)}s)`,
-      });
-
-      const audioUrl = apiClient.getAudioUrl(result.id);
-      setAudio(audioUrl, result.id, selectedProfileId, data.text.substring(0, 50));
-
-      form.reset();
-      setIsExpanded(false);
-    } catch (error) {
-      toast({
-        title: 'Generation failed',
-        description: error instanceof Error ? error.message : 'Failed to generate audio',
-        variant: 'destructive',
-      });
-    } finally {
-      setIsGenerating(false);
-      setDownloadingModelName(null);
-      setDownloadingDisplayName(null);
+      }, 200); // Wait for animation to complete
+      return () => clearTimeout(timeoutId);
     }
+
+    const textarea = textareaRef.current;
+    if (!textarea) return;
+
+    const adjustHeight = () => {
+      textarea.style.height = 'auto';
+      const scrollHeight = textarea.scrollHeight;
+      const minHeight = 100; // Expanded minimum
+      const maxHeight = 300; // Max height in pixels
+      const targetHeight = Math.max(minHeight, Math.min(scrollHeight, maxHeight));
+      textarea.style.height = `${targetHeight}px`;
+
+      // Show scrollbar if content exceeds max height
+      if (scrollHeight > maxHeight) {
+        textarea.style.overflowY = 'auto';
+      } else {
+        textarea.style.overflowY = 'hidden';
+      }
+    };
+
+    // Small delay to let framer animation complete
+    const timeoutId = setTimeout(() => {
+      adjustHeight();
+    }, 200);
+
+    // Adjust on mount and when value changes
+    adjustHeight();
+
+    // Watch for input changes
+    textarea.addEventListener('input', adjustHeight);
+
+    return () => {
+      clearTimeout(timeoutId);
+      textarea.removeEventListener('input', adjustHeight);
+    };
+  }, [isExpanded]);
+
+  async function onSubmit(data: Parameters<typeof handleSubmit>[0]) {
+    await handleSubmit(data, selectedProfileId);
   }
 
   return (
     <motion.div
       ref={containerRef}
-      className="fixed left-[calc(5rem+2rem)] right-auto w-[calc((100%-5rem-4rem)/2-1rem)]"
+      className={cn(
+        'fixed right-auto',
+        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)]',
+      )}
       style={{
-        bottom: isPlayerOpen ? 'calc(7rem + 1.5rem)' : '1.5rem',
+        // On stories route: offset by track editor height when visible
+        // On other routes: offset by audio player height when visible
+        bottom: hasTrackEditor
+          ? `${trackEditorHeight + 24}px`
+          : isPlayerOpen
+            ? 'calc(7rem + 1.5rem)'
+            : '1.5rem',
       }}
     >
       <motion.div
@@ -167,51 +194,145 @@ export function FloatingGenerateBox({ isPlayerOpen }: FloatingGenerateBoxProps)
           <form onSubmit={form.handleSubmit(onSubmit)}>
             <div className="flex gap-2">
               <motion.div
-                className="flex-1"
-                // animate={{ marginBottom: isExpanded ? '0.75rem' : '0' }}
+                className={cn('flex-1', isExpanded && 'mr-12')}
                 transition={{ duration: 0.3, ease: 'easeOut' }}
               >
-                <FormField
-                  control={form.control}
-                  name="text"
-                  render={({ field }) => (
-                    <FormItem>
-                      <FormControl>
-                        <Textarea
-                          placeholder={
-                            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 overflow-hidden transition-all"
-                          style={{
-                            minHeight: isExpanded ? '100px' : '32px',
-                            height: isExpanded ? '100px' : '32px',
-                          }}
-                          disabled={!selectedProfileId}
-                          onClick={() => setIsExpanded(true)}
-                          onFocus={() => setIsExpanded(true)}
-                          {...field}
-                        />
-                      </FormControl>
-                      <FormMessage className="text-xs" />
-                    </FormItem>
-                  )}
-                />
+                {/* Text field - hidden when in instruct mode */}
+                <div style={{ display: isInstructMode ? 'none' : 'block' }}>
+                  <FormField
+                    control={form.control}
+                    name="text"
+                    render={({ field }) => (
+                      <FormItem>
+                        <FormControl>
+                          <motion.div
+                            animate={{
+                              height: isExpanded ? 'auto' : '32px',
+                            }}
+                            transition={{ duration: 0.15, ease: 'easeOut' }}
+                            style={{ overflow: 'hidden' }}
+                          >
+                            <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"
+                              style={{
+                                minHeight: isExpanded ? '100px' : '32px',
+                                maxHeight: '300px',
+                              }}
+                              disabled={!selectedProfileId}
+                              onClick={() => setIsExpanded(true)}
+                              onFocus={() => setIsExpanded(true)}
+                            />
+                          </motion.div>
+                        </FormControl>
+                        <FormMessage className="text-xs" />
+                      </FormItem>
+                    )}
+                  />
+                </div>
+                {/* Instruct field - hidden when in text mode */}
+                <div style={{ display: isInstructMode ? 'block' : 'none' }}>
+                  <FormField
+                    control={form.control}
+                    name="instruct"
+                    render={({ field }) => (
+                      <FormItem>
+                        <FormControl>
+                          <motion.div
+                            animate={{
+                              height: isExpanded ? 'auto' : '32px',
+                            }}
+                            transition={{ duration: 0.15, ease: 'easeOut' }}
+                            style={{ overflow: 'hidden' }}
+                          >
+                            <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="Add delivery instructions..."
+                              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" />
+                      </FormItem>
+                    )}
+                  />
+                </div>
               </motion.div>
 
-              <Button
-                type="submit"
-                disabled={generation.isPending || !selectedProfileId}
-                className="h-10 w-10 rounded-full bg-accent hover:bg-accent/90 hover:scale-105 text-accent-foreground shadow-lg hover:shadow-accent/50 shrink-0 transition-all duration-200"
-                size="icon"
-              >
-                {generation.isPending ? (
-                  <Loader2 className="h-4 w-4 animate-spin" />
-                ) : (
-                  <Sparkles className="h-4 w-4" />
-                )}
-              </Button>
+              <div className="relative shrink-0">
+                <Button
+                  type="submit"
+                  disabled={isPending || !selectedProfileId}
+                  className="h-10 w-10 rounded-full bg-accent hover:bg-accent/90 hover:scale-105 text-accent-foreground shadow-lg hover:shadow-accent/50 transition-all duration-200"
+                  size="icon"
+                >
+                  {isPending ? (
+                    <Loader2 className="h-4 w-4 animate-spin" />
+                  ) : (
+                    <Sparkles className="h-4 w-4" />
+                  )}
+                </Button>
+                <AnimatePresence>
+                  {isExpanded && (
+                    <motion.div
+                      initial={{ opacity: 0, scale: 0.8 }}
+                      animate={{ opacity: 1, scale: 1 }}
+                      exit={{ opacity: 0, scale: 0.8 }}
+                      transition={{ duration: 0.2 }}
+                      className="absolute top-0 right-[calc(100%+0.5rem)]"
+                    >
+                      <Button
+                        type="button"
+                        variant="ghost"
+                        size="icon"
+                        onClick={() => setIsInstructMode(!isInstructMode)}
+                        className={cn(
+                          'h-10 w-10 rounded-full transition-all duration-200',
+                          isInstructMode
+                            ? 'bg-accent text-accent-foreground border border-accent hover:bg-accent/90'
+                            : 'bg-card border border-border hover:bg-background/50',
+                        )}
+                      >
+                        <MessageSquare className="h-4 w-4" />
+                      </Button>
+                    </motion.div>
+                  )}
+                </AnimatePresence>
+              </div>
             </div>
 
             <AnimatePresence>
@@ -223,11 +344,31 @@ export function FloatingGenerateBox({ isPlayerOpen }: FloatingGenerateBoxProps)
                 className=" mt-3"
               >
                 <div className="flex items-center gap-2">
+                  {showVoiceSelector && (
+                    <div className="flex-1">
+                      <Select
+                        value={selectedProfileId || ''}
+                        onValueChange={(value) => setSelectedProfileId(value || null)}
+                      >
+                        <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all w-full">
+                          <SelectValue placeholder="Select a voice..." />
+                        </SelectTrigger>
+                        <SelectContent>
+                          {profiles?.map((profile) => (
+                            <SelectItem key={profile.id} value={profile.id} className="text-xs">
+                              {profile.name}
+                            </SelectItem>
+                          ))}
+                        </SelectContent>
+                      </Select>
+                    </div>
+                  )}
+
                   <FormField
                     control={form.control}
                     name="language"
                     render={({ field }) => (
-                      <FormItem className="flex-1">
+                      <FormItem className="flex-1 space-y-0">
                         <Select onValueChange={field.onChange} defaultValue={field.value}>
                           <FormControl>
                             <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
@@ -251,7 +392,7 @@ export function FloatingGenerateBox({ isPlayerOpen }: FloatingGenerateBoxProps)
                     control={form.control}
                     name="modelSize"
                     render={({ field }) => (
-                      <FormItem className="flex-1">
+                      <FormItem className="flex-1 space-y-0">
                         <Select onValueChange={field.onChange} defaultValue={field.value}>
                           <FormControl>
                             <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">

app/src/components/Generation/GenerationForm.tsx

@@ -1,8 +1,4 @@
-import { zodResolver } from '@hookform/resolvers/zod';
 import { Loader2, Mic } from 'lucide-react';
-import { useState } from 'react';
-import { useForm } from 'react-hook-form';
-import * as z from 'zod';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import {
@@ -23,118 +19,19 @@ import {
   SelectValue,
 } from '@/components/ui/select';
 import { Textarea } from '@/components/ui/textarea';
-import { useToast } from '@/components/ui/use-toast';
-import { apiClient } from '@/lib/api/client';
-import { LANGUAGE_CODES, LANGUAGE_OPTIONS, type LanguageCode } from '@/lib/constants/languages';
-import { useGeneration } from '@/lib/hooks/useGeneration';
-import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
+import { LANGUAGE_OPTIONS } from '@/lib/constants/languages';
+import { useGenerationForm } from '@/lib/hooks/useGenerationForm';
 import { useProfile } from '@/lib/hooks/useProfiles';
-import { useGenerationStore } from '@/stores/generationStore';
-import { usePlayerStore } from '@/stores/playerStore';
 import { useUIStore } from '@/stores/uiStore';
 
-const generationSchema = z.object({
-  text: z.string().min(1, 'Text is required').max(5000),
-  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(),
-});
-
-type GenerationFormValues = z.infer<typeof generationSchema>;
-
 export function GenerationForm() {
   const selectedProfileId = useUIStore((state) => state.selectedProfileId);
   const { data: selectedProfile } = useProfile(selectedProfileId || '');
-  const generation = useGeneration();
-  const { toast } = useToast();
-  const setAudio = usePlayerStore((state) => state.setAudio);
-  const setIsGenerating = useGenerationStore((state) => state.setIsGenerating);
-  const [downloadingModelName, setDownloadingModelName] = useState<string | null>(null);
-  const [downloadingDisplayName, setDownloadingDisplayName] = useState<string | null>(null);
 
-  // Use the download toast hook to show progress when model is downloading
-  useModelDownloadToast({
-    modelName: downloadingModelName || '',
-    displayName: downloadingDisplayName || '',
-    enabled: !!downloadingModelName,
-  });
+  const { form, handleSubmit, isPending } = useGenerationForm();
 
-  const form = useForm<GenerationFormValues>({
-    resolver: zodResolver(generationSchema),
-    defaultValues: {
-      text: '',
-      language: 'en',
-      seed: undefined,
-      modelSize: '1.7B',
-      instruct: '',
-    },
-  });
-
-  async function onSubmit(data: GenerationFormValues) {
-    if (!selectedProfileId) {
-      toast({
-        title: 'No profile selected',
-        description: 'Please select a voice profile from the cards above.',
-        variant: 'destructive',
-      });
-      return;
-    }
-
-    try {
-      setIsGenerating(true);
-
-      // Determine model name and display name
-      const modelName = `qwen-tts-${data.modelSize}`;
-      const displayName = data.modelSize === '1.7B' ? 'Qwen TTS 1.7B' : 'Qwen TTS 0.6B';
-
-      // Check if model is downloaded before starting generation
-      try {
-        const modelStatus = await apiClient.getModelStatus();
-        const model = modelStatus.models.find((m) => m.model_name === modelName);
-
-        if (model && !model.downloaded) {
-          // Model is not downloaded, enable download toast
-          setDownloadingModelName(modelName);
-          setDownloadingDisplayName(displayName);
-        }
-      } catch (error) {
-        // If status check fails, continue anyway - generation will handle it
-        console.error('Failed to check model status:', error);
-      }
-
-      // Proceed with generation (which will trigger download if needed)
-      const result = await generation.mutateAsync({
-        profile_id: selectedProfileId,
-        text: data.text,
-        language: data.language,
-        seed: data.seed,
-        model_size: data.modelSize,
-        instruct: data.instruct || undefined,
-      });
-
-      toast({
-        title: 'Generation complete!',
-        description: `Audio generated (${result.duration.toFixed(2)}s)`,
-      });
-
-      // Autoplay the generated audio
-      const audioUrl = apiClient.getAudioUrl(result.id);
-      setAudio(audioUrl, result.id, selectedProfileId, data.text.substring(0, 50));
-
-      form.reset();
-    } catch (error) {
-      toast({
-        title: 'Generation failed',
-        description: error instanceof Error ? error.message : 'Failed to generate audio',
-        variant: 'destructive',
-      });
-    } finally {
-      setIsGenerating(false);
-      // Clear download state after generation completes
-      setDownloadingModelName(null);
-      setDownloadingDisplayName(null);
-    }
+  async function onSubmit(data: Parameters<typeof handleSubmit>[0]) {
+    await handleSubmit(data, selectedProfileId);
   }
 
   return (
@@ -276,9 +173,9 @@ export function GenerationForm() {
             <Button
               type="submit"
               className="w-full"
-              disabled={generation.isPending || !selectedProfileId}
+              disabled={isPending || !selectedProfileId}
             >
-              {generation.isPending ? (
+              {isPending ? (
                 <>
                   <Loader2 className="mr-2 h-4 w-4 animate-spin" />
                   Generating...

app/src/components/History/HistoryTable.tsx

@@ -1,4 +1,12 @@
-import { AudioWaveform, Download, FileArchive, MoreHorizontal, Play, Trash2 } from 'lucide-react';
+import {
+  AudioWaveform,
+  Download,
+  FileArchive,
+  Loader2,
+  MoreHorizontal,
+  Play,
+  Trash2,
+} from 'lucide-react';
 import { useEffect, useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
 import {
@@ -16,7 +24,9 @@ import {
   DropdownMenuTrigger,
 } from '@/components/ui/dropdown-menu';
 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,
@@ -32,17 +42,27 @@ import { usePlayerStore } from '@/stores/playerStore';
 // OLD TABLE-BASED COMPONENT - REMOVED (can be found in git history)
 // This is the new alternate history view with fixed height rows
 
-// NEW ALTERNATE HISTORY VIEW - FIXED HEIGHT ROWS
+// NEW ALTERNATE HISTORY VIEW - FIXED HEIGHT ROWS WITH INFINITE SCROLL
 export function HistoryTable() {
-  const [page, _setPage] = useState(0);
+  const [page, setPage] = useState(0);
+  const [allHistory, setAllHistory] = useState<HistoryResponse[]>([]);
+  const [total, setTotal] = useState(0);
   const [isScrolled, setIsScrolled] = useState(false);
   const scrollRef = useRef<HTMLDivElement>(null);
+  const loadMoreRef = useRef<HTMLDivElement>(null);
   const fileInputRef = useRef<HTMLInputElement>(null);
   const [importDialogOpen, setImportDialogOpen] = useState(false);
   const [selectedFile, setSelectedFile] = useState<File | null>(null);
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [generationToDelete, setGenerationToDelete] = useState<{ id: string; name: string } | null>(null);
   const limit = 20;
+  const { toast } = useToast();
 
-  const { data: historyData, isLoading } = useHistory({
+  const {
+    data: historyData,
+    isLoading,
+    isFetching,
+  } = useHistory({
     limit,
     offset: page * limit,
   });
@@ -51,13 +71,63 @@ export function HistoryTable() {
   const exportGeneration = useExportGeneration();
   const exportGenerationAudio = useExportGenerationAudio();
   const importGeneration = useImportGeneration();
-  const setAudio = usePlayerStore((state) => state.setAudio);
+  const setAudioWithAutoPlay = usePlayerStore((state) => state.setAudioWithAutoPlay);
   const restartCurrentAudio = usePlayerStore((state) => state.restartCurrentAudio);
   const currentAudioId = usePlayerStore((state) => state.audioId);
   const isPlaying = usePlayerStore((state) => state.isPlaying);
   const audioUrl = usePlayerStore((state) => state.audioUrl);
   const isPlayerVisible = !!audioUrl;
 
+  // Update accumulated history when new data arrives
+  useEffect(() => {
+    if (historyData?.items) {
+      setTotal(historyData.total);
+      if (page === 0) {
+        // Reset to first page
+        setAllHistory(historyData.items);
+      } else {
+        // Append new items, avoiding duplicates
+        setAllHistory((prev) => {
+          const existingIds = new Set(prev.map((item) => item.id));
+          const newItems = historyData.items.filter((item) => !existingIds.has(item.id));
+          return [...prev, ...newItems];
+        });
+      }
+    }
+  }, [historyData, page]);
+
+  // Reset to page 0 when deletions or imports occur
+  useEffect(() => {
+    if (deleteGeneration.isSuccess || importGeneration.isSuccess) {
+      setPage(0);
+      setAllHistory([]);
+    }
+  }, [deleteGeneration.isSuccess, importGeneration.isSuccess]);
+
+  // Intersection Observer for infinite scroll
+  useEffect(() => {
+    const loadMoreEl = loadMoreRef.current;
+    if (!loadMoreEl) return;
+
+    const observer = new IntersectionObserver(
+      (entries) => {
+        const target = entries[0];
+        if (target.isIntersecting && !isFetching && allHistory.length < total) {
+          setPage((prev) => prev + 1);
+        }
+      },
+      {
+        root: scrollRef.current,
+        rootMargin: '100px',
+        threshold: 0.1,
+      },
+    );
+
+    observer.observe(loadMoreEl);
+    return () => observer.disconnect();
+  }, [isFetching, allHistory.length, total]);
+
+  // Track scroll position for gradient effect
   useEffect(() => {
     const scrollEl = scrollRef.current;
     if (!scrollEl) return;
@@ -75,9 +145,9 @@ export function HistoryTable() {
     if (currentAudioId === audioId) {
       restartCurrentAudio();
     } else {
-      // Otherwise, load the new audio
+      // Otherwise, load the new audio and auto-play it
       const audioUrl = apiClient.getAudioUrl(audioId);
-      setAudio(audioUrl, audioId, profileId, text.substring(0, 50));
+      setAudioWithAutoPlay(audioUrl, audioId, profileId, text.substring(0, 50));
     }
   };
 
@@ -86,7 +156,11 @@ export function HistoryTable() {
       { generationId, text },
       {
         onError: (error) => {
-          alert(`Failed to download audio: ${error.message}`);
+          toast({
+            title: 'Failed to download audio',
+            description: error.message,
+            variant: 'destructive',
+          });
         },
       },
     );
@@ -97,26 +171,26 @@ export function HistoryTable() {
       { generationId, text },
       {
         onError: (error) => {
-          alert(`Failed to export generation: ${error.message}`);
+          toast({
+            title: 'Failed to export generation',
+            description: error.message,
+            variant: 'destructive',
+          });
         },
       },
     );
   };
 
-  const _handleImportClick = () => {
-    file_handleImportClickk.click();
+  const handleDeleteClick = (generationId: string, profileName: string) => {
+    setGenerationToDelete({ id: generationId, name: profileName });
+    setDeleteDialogOpen(true);
   };
 
-  const _handleFileChange = (_e: React.ChangeEvent<HTMLInputElement>) => {
-    cons_handleFileChangeet.files?.[0];
-    if (file) {
-      // Validate file extension
-      if (!file.name.endsWith('.voicebox.zip')) {
-        alert('Please select a valid .voicebox.zip file');
-        return;
-      }
-      setSelectedFile(file);
-      setImportDialogOpen(true);
+  const handleDeleteConfirm = () => {
+    if (generationToDelete) {
+      deleteGeneration.mutate(generationToDelete.id);
+      setDeleteDialogOpen(false);
+      setGenerationToDelete(null);
     }
   };
 
@@ -129,42 +203,35 @@ export function HistoryTable() {
           if (fileInputRef.current) {
             fileInputRef.current.value = '';
           }
-          alert(data.message || 'Generation imported successfully');
+          toast({
+            title: 'Generation imported',
+            description: data.message || 'Generation imported successfully',
+          });
         },
         onError: (error) => {
-          alert(`Failed to import generation: ${error.message}`);
+          toast({
+            title: 'Failed to import generation',
+            description: error.message,
+            variant: 'destructive',
+          });
         },
       });
     }
   };
 
-  if (isLoading) {
-    return null;
+  if (isLoading && page === 0) {
+    return (
+      <div className="flex items-center justify-center h-full">
+        <Loader2 className="h-8 w-8 animate-spin text-muted-foreground" />
+      </div>
+    );
   }
 
-  const history = historyData?.items || [];
-  const total = historyData?.total || 0;
-  const _hasMore = history.length === limit && (page + 1) * limit < total;
+  const history = allHistory;
+  const hasMore = allHistory.length < total;
 
   return (
     <div className="flex flex-col h-full min-h-0 relative">
-      {/* <div className="flex justify-between items-center mb-4 shrink-0">
-        <h2 className="text-2xl font-bold">History</h2>
-        <div className="flex gap-2">
-          <Button variant="outline" onClick={handleImportClick}>
-            <Upload className="mr-2 h-4 w-4" />
-            Import Generation
-          </Button>
-          <input
-            ref={fileInputRef}
-            type="file"
-            accept=".voicebox.zip"
-            onChange={handleFileChange}
-            className="hidden"
-          />
-        </div>
-      </div> */}
-
       {history.length === 0 ? (
         <div className="text-center py-12 px-5 border-2 border-dashed mb-5 border-muted rounded-md text-muted-foreground flex-1 flex items-center justify-center">
           No voice generations, yet...
@@ -225,11 +292,16 @@ export function HistoryTable() {
                     <Textarea
                       value={gen.text}
                       className="flex-1 resize-none text-sm text-muted-foreground select-text"
+                      readOnly
                     />
                   </div>
 
                   {/* Far right - Ellipsis actions */}
-                  <div className="w-10 shrink-0 flex justify-end">
+                  <div
+                    className="w-10 shrink-0 flex justify-end"
+                    onMouseDown={(e) => e.stopPropagation()}
+                    onClick={(e) => e.stopPropagation()}
+                  >
                     <DropdownMenu>
                       <DropdownMenuTrigger asChild>
                         <Button
@@ -237,7 +309,6 @@ export function HistoryTable() {
                           size="icon"
                           className="h-8 w-8"
                           aria-label="Actions"
-                          onClick={(e) => e.stopPropagation()}
                         >
                           <MoreHorizontal className="h-4 w-4" />
                         </Button>
@@ -264,7 +335,7 @@ export function HistoryTable() {
                           Export Package
                         </DropdownMenuItem>
                         <DropdownMenuItem
-                          onClick={() => deleteGeneration.mutate(gen.id)}
+                          onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
                           disabled={deleteGeneration.isPending}
                           className="text-destructive focus:text-destructive"
                         >
@@ -277,10 +348,53 @@ export function HistoryTable() {
                 </div>
               );
             })}
+
+            {/* Load more trigger element */}
+            {hasMore && (
+              <div ref={loadMoreRef} className="flex items-center justify-center py-4">
+                {isFetching && <Loader2 className="h-6 w-6 animate-spin text-muted-foreground" />}
+              </div>
+            )}
+
+            {/* End of list indicator */}
+            {!hasMore && history.length > 0 && (
+              <div className="text-center py-4 text-xs text-muted-foreground">
+                You've reached the end
+              </div>
+            )}
           </div>
         </>
       )}
 
+      <Dialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>Delete Generation</DialogTitle>
+            <DialogDescription>
+              Are you sure you want to delete this generation from "{generationToDelete?.name}"? This action cannot be undone.
+            </DialogDescription>
+          </DialogHeader>
+          <DialogFooter>
+            <Button
+              variant="outline"
+              onClick={() => {
+                setDeleteDialogOpen(false);
+                setGenerationToDelete(null);
+              }}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="destructive"
+              onClick={handleDeleteConfirm}
+              disabled={deleteGeneration.isPending}
+            >
+              {deleteGeneration.isPending ? 'Deleting...' : 'Delete'}
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+
       <Dialog open={importDialogOpen} onOpenChange={setImportDialogOpen}>
         <DialogContent>
           <DialogHeader>

app/src/components/MainEditor/MainEditor.tsx

@@ -11,6 +11,7 @@ import {
   DialogHeader,
   DialogTitle,
 } 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';
@@ -27,6 +28,7 @@ export function MainEditor() {
   const fileInputRef = useRef<HTMLInputElement>(null);
   const [importDialogOpen, setImportDialogOpen] = useState(false);
   const [selectedFile, setSelectedFile] = useState<File | null>(null);
+  const { toast } = useToast();
 
   const handleImportClick = () => {
     fileInputRef.current?.click();
@@ -36,7 +38,11 @@ export function MainEditor() {
     const file = e.target.files?.[0];
     if (file) {
       if (!file.name.endsWith('.voicebox.zip')) {
-        alert('Please select a valid .voicebox.zip file');
+        toast({
+          title: 'Invalid file type',
+          description: 'Please select a valid .voicebox.zip file',
+          variant: 'destructive',
+        });
         return;
       }
       setSelectedFile(file);
@@ -53,9 +59,17 @@ export function MainEditor() {
           if (fileInputRef.current) {
             fileInputRef.current.value = '';
           }
+          toast({
+            title: 'Profile imported',
+            description: 'Voice profile imported successfully',
+          });
         },
         onError: (error) => {
-          alert(`Failed to import profile: ${error.message}`);
+          toast({
+            title: 'Failed to import profile',
+            description: error.message,
+            variant: 'destructive',
+          });
         },
       });
     }
@@ -102,15 +116,9 @@ export function MainEditor() {
           )}
         >
           <div className="flex flex-col gap-6">
-            {/* Profiles - Top Left */}
             <div className="shrink-0 flex flex-col">
               <ProfileList />
             </div>
-
-            {/* Generator - Bottom Left */}
-            {/* <div className="shrink-0">
-              <GenerationForm />
-            </div> */}
           </div>
         </div>
       </div>

app/src/components/ServerSettings/ConnectionForm.tsx

@@ -17,7 +17,7 @@ import { Input } from '@/components/ui/input';
 import { Checkbox } from '@/components/ui/checkbox';
 import { useToast } from '@/components/ui/use-toast';
 import { useServerStore } from '@/stores/serverStore';
-import { setKeepServerRunning } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 
 const connectionSchema = z.object({
   serverUrl: z.string().url('Please enter a valid URL'),
@@ -26,6 +26,7 @@ const connectionSchema = z.object({
 type ConnectionFormValues = z.infer<typeof connectionSchema>;
 
 export function ConnectionForm() {
+  const platform = usePlatform();
   const serverUrl = useServerStore((state) => state.serverUrl);
   const setServerUrl = useServerStore((state) => state.setServerUrl);
   const keepServerRunningOnClose = useServerStore((state) => state.keepServerRunningOnClose);
@@ -89,7 +90,7 @@ export function ConnectionForm() {
               checked={keepServerRunningOnClose}
               onCheckedChange={(checked: boolean) => {
                 setKeepServerRunningOnClose(checked);
-                setKeepServerRunning(checked).catch((error) => {
+                platform.lifecycle.setKeepServerRunning(checked).catch((error) => {
                   console.error('Failed to sync setting to Rust:', error);
                 });
                 toast({

app/src/components/ServerSettings/ModelManagement.tsx

@@ -1,6 +1,6 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
 import { Download, Loader2, Trash2 } from 'lucide-react';
-import { useState } from 'react';
+import { useCallback, useState } from 'react';
 import {
   AlertDialog,
   AlertDialogAction,
@@ -17,7 +17,6 @@ import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/com
 import { useToast } from '@/components/ui/use-toast';
 import { apiClient } from '@/lib/api/client';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
-import { ModelProgress } from './ModelProgress';
 
 export function ModelManagement() {
   const { toast } = useToast();
@@ -27,15 +26,36 @@ export function ModelManagement() {
 
   const { data: modelStatus, isLoading } = useQuery({
     queryKey: ['modelStatus'],
-    queryFn: () => apiClient.getModelStatus(),
+    queryFn: async () => {
+      console.log('[Query] Fetching model status');
+      const result = await apiClient.getModelStatus();
+      console.log('[Query] Model status fetched:', result);
+      return result;
+    },
     refetchInterval: 5000, // Refresh every 5 seconds
   });
 
+  // Callbacks for download completion
+  const handleDownloadComplete = useCallback(() => {
+    console.log('[ModelManagement] Download complete, clearing state');
+    setDownloadingModel(null);
+    setDownloadingDisplayName(null);
+    queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
+  }, [queryClient]);
+
+  const handleDownloadError = useCallback(() => {
+    console.log('[ModelManagement] Download error, clearing state');
+    setDownloadingModel(null);
+    setDownloadingDisplayName(null);
+  }, []);
+
   // Use progress toast hook for the downloading model
   useModelDownloadToast({
     modelName: downloadingModel || '',
     displayName: downloadingDisplayName || '',
     enabled: !!downloadingModel && !!downloadingDisplayName,
+    onComplete: handleDownloadComplete,
+    onError: handleDownloadError,
   });
 
   const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
@@ -45,44 +65,69 @@ export function ModelManagement() {
     sizeMb?: number;
   } | null>(null);
 
-  const downloadMutation = useMutation({
-    mutationFn: (modelName: string) => {
+  const handleDownload = async (modelName: string) => {
+    console.log('[Download] Button clicked for:', modelName, 'at', new Date().toISOString());
+    
+    // Find display name
+    const model = modelStatus?.models.find((m) => m.model_name === modelName);
+    const displayName = model?.display_name || modelName;
+    
+    try {
+      // IMPORTANT: Call the API FIRST before setting state
+      // Setting state enables the SSE EventSource in useModelDownloadToast,
+      // which can block/delay the download fetch due to HTTP/1.1 connection limits
+      console.log('[Download] Calling download API for:', modelName);
+      const result = await apiClient.triggerModelDownload(modelName);
+      console.log('[Download] Download API responded:', result);
+      
+      // NOW set state to enable SSE tracking (after download has started on backend)
       setDownloadingModel(modelName);
-      // Find display name from model status
-      const model = modelStatus?.models.find((m) => m.model_name === modelName);
-      setDownloadingDisplayName(model?.display_name || modelName);
-      return apiClient.triggerModelDownload(modelName);
-    },
-    onSuccess: () => {
-      // Download completed - clear state and refetch status
-      setDownloadingModel(null);
-      setDownloadingDisplayName(null);
+      setDownloadingDisplayName(displayName);
+      
+      // Download initiated successfully - state will be cleared when SSE reports completion
+      // or by the polling interval detecting the model is downloaded
       queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
-    },
-    onError: (error: Error) => {
+    } catch (error) {
+      console.error('[Download] Download failed:', error);
       setDownloadingModel(null);
       setDownloadingDisplayName(null);
       toast({
         title: 'Download failed',
-        description: error.message,
+        description: error instanceof Error ? error.message : 'Unknown error',
         variant: 'destructive',
       });
-    },
-  });
+    }
+  };
 
   const deleteMutation = useMutation({
-    mutationFn: (modelName: string) => apiClient.deleteModel(modelName),
-    onSuccess: () => {
+    mutationFn: async (modelName: string) => {
+      console.log('[Delete] Deleting model:', modelName);
+      const result = await apiClient.deleteModel(modelName);
+      console.log('[Delete] Model deleted successfully:', modelName);
+      return result;
+    },
+    onSuccess: async (_data, _modelName) => {
+      console.log('[Delete] onSuccess - showing toast and invalidating queries');
       toast({
         title: 'Model deleted',
         description: `${modelToDelete?.displayName || 'Model'} has been deleted successfully.`,
       });
       setDeleteDialogOpen(false);
       setModelToDelete(null);
-      // Refetch status to update UI
-      queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
+      // Invalidate AND explicitly refetch to ensure UI updates
+      // Using refetchType: 'all' ensures we refetch even if the query is stale
+      console.log('[Delete] Invalidating modelStatus query');
+      await queryClient.invalidateQueries({ 
+        queryKey: ['modelStatus'],
+        refetchType: 'all',
+      });
+      // Also explicitly refetch to guarantee fresh data
+      console.log('[Delete] Explicitly refetching modelStatus query');
+      await queryClient.refetchQueries({ queryKey: ['modelStatus'] });
+      console.log('[Delete] Query refetched');
     },
     onError: (error: Error) => {
+      console.log('[Delete] onError:', error);
       toast({
         title: 'Delete failed',
         description: error.message,
@@ -124,7 +169,7 @@ export function ModelManagement() {
                     <ModelItem
                       key={model.model_name}
                       model={model}
-                      onDownload={() => downloadMutation.mutate(model.model_name)}
+                      onDownload={() => handleDownload(model.model_name)}
                       onDelete={() => {
                         setModelToDelete({
                           name: model.model_name,
@@ -152,7 +197,7 @@ export function ModelManagement() {
                     <ModelItem
                       key={model.model_name}
                       model={model}
-                      onDownload={() => downloadMutation.mutate(model.model_name)}
+                      onDownload={() => handleDownload(model.model_name)}
                       onDelete={() => {
                         setModelToDelete({
                           name: model.model_name,
@@ -168,21 +213,6 @@ export function ModelManagement() {
               </div>
             </div>
 
-            {/* Progress indicators */}
-            <div className="pt-4 border-t">
-              <h3 className="text-sm font-semibold mb-3 text-muted-foreground">
-                Download Progress
-              </h3>
-              <div className="space-y-2">
-                {modelStatus.models.map((model) => (
-                  <ModelProgress
-                    key={model.model_name}
-                    modelName={model.model_name}
-                    displayName={model.display_name}
-                  />
-                ))}
-              </div>
-            </div>
           </div>
         ) : null}
       </CardContent>
@@ -235,16 +265,20 @@ interface ModelItemProps {
     model_name: string;
     display_name: string;
     downloaded: boolean;
+    downloading?: boolean;  // From server - true if download in progress
     size_mb?: number;
     loaded: boolean;
   };
   onDownload: () => void;
   onDelete: () => void;
-  isDownloading: boolean;
+  isDownloading: boolean;  // Local state - true if user just clicked download
   formatSize: (sizeMb?: number) => string;
 }
 
 function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: ModelItemProps) {
+  // Use server's downloading state OR local state (for immediate feedback before server updates)
+  const showDownloading = model.downloading || isDownloading;
+  
   return (
     <div className="flex items-center justify-between p-3 border rounded-lg">
       <div className="flex-1">
@@ -255,20 +289,21 @@ function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: M
               Loaded
             </Badge>
           )}
-          {model.downloaded && !model.loaded && (
+          {/* Only show Downloaded if actually downloaded AND not downloading */}
+          {model.downloaded && !model.loaded && !showDownloading && (
             <Badge variant="secondary" className="text-xs">
               Downloaded
             </Badge>
           )}
         </div>
-        {model.downloaded && model.size_mb && (
+        {model.downloaded && model.size_mb && !showDownloading && (
           <div className="text-xs text-muted-foreground mt-1">
             Size: {formatSize(model.size_mb)}
           </div>
         )}
       </div>
       <div className="flex items-center gap-2">
-        {model.downloaded ? (
+        {model.downloaded && !showDownloading ? (
           <div className="flex items-center gap-2">
             <div className="flex items-center gap-1 text-sm text-muted-foreground">
               <span>Ready</span>
@@ -283,19 +318,15 @@ function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: M
               <Trash2 className="h-4 w-4" />
             </Button>
           </div>
+        ) : showDownloading ? (
+          <Button size="sm" variant="outline" disabled>
+            <Loader2 className="h-4 w-4 mr-2 animate-spin" />
+            Downloading...
+          </Button>
         ) : (
-          <Button size="sm" onClick={onDownload} disabled={isDownloading} variant="outline">
-            {isDownloading ? (
-              <>
-                <Loader2 className="h-4 w-4 mr-2 animate-spin" />
-                Downloading...
-              </>
-            ) : (
-              <>
-                <Download className="h-4 w-4 mr-2" />
-                Download
-              </>
-            )}
+          <Button size="sm" onClick={onDownload} variant="outline">
+            <Download className="h-4 w-4 mr-2" />
+            Download
           </Button>
         )}
       </div>

app/src/components/ServerSettings/ModelProgress.tsx

@@ -8,15 +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 [isSubscribed, setIsSubscribed] = useState(false);
   const serverUrl = useServerStore((state) => state.serverUrl);
 
   useEffect(() => {
-    if (!serverUrl || isSubscribed) 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}`);
@@ -28,8 +36,8 @@ 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();
-          setIsSubscribed(false);
         }
       } catch (error) {
         console.error('Error parsing progress event:', error);
@@ -37,18 +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();
-      setIsSubscribed(false);
     };
 
-    setIsSubscribed(true);
-
     return () => {
+      console.log(`[ModelProgress] Cleanup - closing SSE for ${modelName}`);
       eventSource.close();
-      setIsSubscribed(false);
     };
-  }, [serverUrl, modelName, isSubscribed]);
+  }, [serverUrl, modelName, isDownloading]);
 
   // Don't render if no progress or if complete/error and some time has passed
   if (

app/src/components/ServerSettings/UpdateStatus.tsx

@@ -1,21 +1,23 @@
-import { getVersion } from '@tauri-apps/api/app';
-import { RefreshCw, Download, AlertCircle } from 'lucide-react';
+import { AlertCircle, Download, RefreshCw } from 'lucide-react';
 import { useEffect, useState } from 'react';
 import { Badge } from '@/components/ui/badge';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { Progress } from '@/components/ui/progress';
 import { useAutoUpdater } from '@/hooks/useAutoUpdater';
+import { usePlatform } from '@/platform/PlatformContext';
 
 export function UpdateStatus() {
+  const platform = usePlatform();
   const { status, checkForUpdates, downloadAndInstall, restartAndInstall } = useAutoUpdater(false);
   const [currentVersion, setCurrentVersion] = useState<string>('');
 
   useEffect(() => {
-    getVersion()
+    platform.metadata
+      .getVersion()
       .then(setCurrentVersion)
-      .catch(() => setCurrentVersion('0.1.0'));
-  }, []);
+      .catch(() => setCurrentVersion('Unknown'));
+  }, [platform]);
 
   return (
     <Card>
@@ -93,7 +95,7 @@ export function UpdateStatus() {
         )}
 
         {status.readyToInstall && (
-          <div className="space-y-3 p-4 border rounded-lg bg-green-500/10 border-green-500/20">
+          <div className="space-y-3 p-4 border rounded-lg bg-accent/30 border-accent/50">
             <div className="flex items-center gap-2">
               <div>
                 <div className="font-semibold">Update Ready to Install</div>

app/src/components/ServerTab/ServerTab.tsx

@@ -1,16 +1,17 @@
 import { ConnectionForm } from '@/components/ServerSettings/ConnectionForm';
 import { ServerStatus } from '@/components/ServerSettings/ServerStatus';
 import { UpdateStatus } from '@/components/ServerSettings/UpdateStatus';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 
 export function ServerTab() {
+  const platform = usePlatform();
   return (
     <div className="space-y-4 overflow-y-auto flex flex-col">
       <div className="grid gap-4 md:grid-cols-2">
         <ConnectionForm />
         <ServerStatus />
       </div>
-      {isTauri() && <UpdateStatus />}
+      {platform.metadata.isTauri && <UpdateStatus />}
       <div className="py-8 text-center text-sm text-muted-foreground">
         Created by{' '}
         <a

app/src/components/Sidebar.tsx

@@ -1,27 +1,28 @@
-import { Box, Loader2, Mic, Server, Speaker, Volume2 } from 'lucide-react';
+import { Link, useMatchRoute } from '@tanstack/react-router';
+import { Box, BookOpen, Loader2, Mic, Server, Speaker, Volume2 } from 'lucide-react';
 import voiceboxLogo from '@/assets/voicebox-logo.png';
 import { cn } from '@/lib/utils/cn';
 import { useGenerationStore } from '@/stores/generationStore';
 import { usePlayerStore } from '@/stores/playerStore';
 
 interface SidebarProps {
-  activeTab: string;
-  onTabChange: (tab: string) => void;
   isMacOS?: boolean;
 }
 
 const tabs = [
-  { id: 'main', icon: Volume2, label: 'Generate' },
-  { id: 'voices', icon: Mic, label: 'Voices' },
-  { id: 'audio', icon: Speaker, label: 'Audio' },
-  { id: 'models', icon: Box, label: 'Models' },
-  { id: 'server', icon: Server, label: 'Server' },
+  { id: 'main', path: '/', icon: Volume2, label: 'Generate' },
+  { id: 'stories', path: '/stories', icon: BookOpen, label: 'Stories' },
+  { id: 'voices', path: '/voices', icon: Mic, label: 'Voices' },
+  { id: 'audio', path: '/audio', icon: Speaker, label: 'Audio' },
+  { id: 'models', path: '/models', icon: Box, label: 'Models' },
+  { id: 'server', path: '/server', icon: Server, label: 'Server' },
 ];
 
-export function Sidebar({ activeTab, onTabChange, isMacOS }: SidebarProps) {
+export function Sidebar({ isMacOS }: SidebarProps) {
   const isGenerating = useGenerationStore((state) => state.isGenerating);
   const audioUrl = usePlayerStore((state) => state.audioUrl);
   const isPlayerVisible = !!audioUrl;
+  const matchRoute = useMatchRoute();
 
   return (
     <div
@@ -39,13 +40,16 @@ export function Sidebar({ activeTab, onTabChange, isMacOS }: SidebarProps) {
       <div className="flex flex-col gap-3">
         {tabs.map((tab) => {
           const Icon = tab.icon;
-          const isActive = activeTab === tab.id;
+          // For index route, use exact match; for others, use default matching
+          const isActive =
+            tab.path === '/'
+              ? matchRoute({ to: '/', exact: true })
+              : matchRoute({ to: tab.path });
 
           return (
-            <button
+            <Link
               key={tab.id}
-              type="button"
-              onClick={() => onTabChange(tab.id)}
+              to={tab.path}
               className={cn(
                 'w-12 h-12 rounded-full flex items-center justify-center transition-all duration-200',
                 'hover:bg-muted/50',
@@ -55,7 +59,7 @@ export function Sidebar({ activeTab, onTabChange, isMacOS }: SidebarProps) {
               aria-label={tab.label}
             >
               <Icon className="h-5 w-5" />
-            </button>
+            </Link>
           );
         })}
       </div>

app/src/components/StoriesTab/StoriesTab.tsx

@@ -0,0 +1,25 @@
+import { FloatingGenerateBox } from '@/components/Generation/FloatingGenerateBox';
+import { StoryContent } from './StoryContent';
+import { StoryList } from './StoryList';
+
+export function StoriesTab() {
+  return (
+    <div className="flex flex-col h-full min-h-0 overflow-hidden">
+      {/* Main content area */}
+      <div className="flex-1 min-h-0 flex gap-6 overflow-hidden relative">
+        {/* Left Column - Story List */}
+        <div className="flex flex-col min-h-0 overflow-hidden w-full max-w-[360px] shrink-0">
+          <StoryList />
+        </div>
+
+        {/* Right Column - Story Content */}
+        <div className="flex flex-col min-h-0 overflow-hidden flex-1">
+          <StoryContent />
+        </div>
+
+        {/* Floating Generate Box - position is managed via storyStore.trackEditorHeight */}
+        <FloatingGenerateBox showVoiceSelector />
+      </div>
+    </div>
+  );
+}

app/src/components/StoriesTab/StoryChatItem.tsx

@@ -0,0 +1,166 @@
+import { useSortable } from '@dnd-kit/sortable';
+import { CSS } from '@dnd-kit/utilities';
+import { GripVertical, Mic, MoreHorizontal, Play, Trash2 } from 'lucide-react';
+import { useState } from 'react';
+import { Button } from '@/components/ui/button';
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuTrigger,
+} from '@/components/ui/dropdown-menu';
+import { Textarea } from '@/components/ui/textarea';
+import type { StoryItemDetail } from '@/lib/api/types';
+import { cn } from '@/lib/utils/cn';
+import { useStoryStore } from '@/stores/storyStore';
+import { useServerStore } from '@/stores/serverStore';
+
+interface StoryChatItemProps {
+  item: StoryItemDetail;
+  storyId: string;
+  index: number;
+  onRemove: () => void;
+  currentTimeMs: number;
+  isPlaying: boolean;
+  dragHandleProps?: React.HTMLAttributes<HTMLButtonElement>;
+  isDragging?: boolean;
+}
+
+export function StoryChatItem({
+  item,
+  onRemove,
+  currentTimeMs,
+  isPlaying,
+  dragHandleProps,
+  isDragging,
+}: StoryChatItemProps) {
+  const seek = useStoryStore((state) => state.seek);
+  const serverUrl = useServerStore((state) => state.serverUrl);
+  const [avatarError, setAvatarError] = useState(false);
+
+  const avatarUrl = `${serverUrl}/profiles/${item.profile_id}/avatar`;
+
+  // Check if this item is currently playing based on timecode
+  const itemStartMs = item.start_time_ms;
+  const itemEndMs = item.start_time_ms + item.duration * 1000;
+  const isCurrentlyPlaying = isPlaying && currentTimeMs >= itemStartMs && currentTimeMs < itemEndMs;
+
+  const handlePlay = () => {
+    // Seek to the start of this item
+    seek(itemStartMs);
+  };
+
+  const formatTime = (ms: number): string => {
+    const totalSeconds = Math.floor(ms / 1000);
+    const minutes = Math.floor(totalSeconds / 60);
+    const seconds = totalSeconds % 60;
+    const milliseconds = Math.floor((ms % 1000) / 100);
+    return `${minutes}:${seconds.toString().padStart(2, '0')}.${milliseconds}`;
+  };
+
+  return (
+    <div
+      className={cn(
+        'flex items-start gap-3 p-4 rounded-lg border transition-colors',
+        isCurrentlyPlaying && 'bg-muted/70 border-primary',
+        !isCurrentlyPlaying && 'hover:bg-muted/50',
+        isDragging && 'opacity-50 shadow-lg',
+      )}
+    >
+      {/* Drag Handle */}
+      {dragHandleProps && (
+        <button
+          type="button"
+          className="shrink-0 cursor-grab active:cursor-grabbing touch-none text-muted-foreground hover:text-foreground transition-colors"
+          {...dragHandleProps}
+        >
+          <GripVertical className="h-5 w-5" />
+        </button>
+      )}
+
+      {/* Voice Avatar */}
+      <div className="shrink-0">
+        <div className="h-10 w-10 rounded-full bg-muted flex items-center justify-center overflow-hidden">
+          {!avatarError ? (
+            <img
+              src={avatarUrl}
+              alt={`${item.profile_name} avatar`}
+              className={cn(
+                'h-full w-full object-cover transition-all duration-200',
+                !isCurrentlyPlaying && 'grayscale'
+              )}
+              onError={() => setAvatarError(true)}
+            />
+          ) : (
+            <Mic className="h-5 w-5 text-muted-foreground" />
+          )}
+        </div>
+      </div>
+
+      {/* Content */}
+      <div className="flex-1 min-w-0">
+        <div className="flex items-center gap-2 mb-2">
+          <span className="font-medium text-sm">{item.profile_name}</span>
+          <span className="text-xs text-muted-foreground">{item.language}</span>
+          <span className="text-xs text-muted-foreground tabular-nums ml-auto">
+            {formatTime(itemStartMs)}
+          </span>
+        </div>
+        <Textarea
+          value={item.text}
+          className="flex-1 resize-none text-sm text-muted-foreground select-text bg-card cursor-text"
+          readOnly
+          onDoubleClick={handlePlay}
+        />
+      </div>
+
+      {/* Actions */}
+      <div className="shrink-0">
+        <DropdownMenu>
+          <DropdownMenuTrigger asChild>
+            <Button variant="ghost" size="icon" className="h-8 w-8" aria-label="Actions">
+              <MoreHorizontal className="h-4 w-4" />
+            </Button>
+          </DropdownMenuTrigger>
+          <DropdownMenuContent align="end">
+            <DropdownMenuItem onClick={handlePlay}>
+              <Play className="mr-2 h-4 w-4" />
+              Play from here
+            </DropdownMenuItem>
+            <DropdownMenuItem onClick={onRemove} className="text-destructive focus:text-destructive">
+              <Trash2 className="mr-2 h-4 w-4" />
+              Remove from Story
+            </DropdownMenuItem>
+          </DropdownMenuContent>
+        </DropdownMenu>
+      </div>
+    </div>
+  );
+}
+
+// Sortable wrapper component
+export function SortableStoryChatItem(props: Omit<StoryChatItemProps, 'dragHandleProps' | 'isDragging'>) {
+  const {
+    attributes,
+    listeners,
+    setNodeRef,
+    transform,
+    transition,
+    isDragging,
+  } = useSortable({ id: props.item.generation_id });
+
+  const style = {
+    transform: CSS.Transform.toString(transform),
+    transition,
+  };
+
+  return (
+    <div ref={setNodeRef} style={style} {...attributes}>
+      <StoryChatItem
+        {...props}
+        dragHandleProps={listeners}
+        isDragging={isDragging}
+      />
+    </div>
+  );
+}

app/src/components/StoriesTab/StoryContent.tsx

@@ -0,0 +1,376 @@
+import {
+  closestCenter,
+  DndContext,
+  type DragEndEvent,
+  KeyboardSensor,
+  PointerSensor,
+  useSensor,
+  useSensors,
+} from '@dnd-kit/core';
+import {
+  arrayMove,
+  SortableContext,
+  sortableKeyboardCoordinates,
+  verticalListSortingStrategy,
+} from '@dnd-kit/sortable';
+import { Download, Plus } from 'lucide-react';
+import { useEffect, useMemo, useRef, useState } from 'react';
+import { Button } from '@/components/ui/button';
+import { Input } from '@/components/ui/input';
+import { Popover, PopoverContent, PopoverTrigger } from '@/components/ui/popover';
+import { useToast } from '@/components/ui/use-toast';
+import { useHistory } from '@/lib/hooks/useHistory';
+import {
+  useAddStoryItem,
+  useExportStoryAudio,
+  useRemoveStoryItem,
+  useReorderStoryItems,
+  useStory,
+} from '@/lib/hooks/useStories';
+import { useStoryPlayback } from '@/lib/hooks/useStoryPlayback';
+import { useStoryStore } from '@/stores/storyStore';
+import { SortableStoryChatItem } from './StoryChatItem';
+
+export function StoryContent() {
+  const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
+  const { data: story, isLoading } = useStory(selectedStoryId);
+  const removeItem = useRemoveStoryItem();
+  const reorderItems = useReorderStoryItems();
+  const exportAudio = useExportStoryAudio();
+  const addStoryItem = useAddStoryItem();
+  const { toast } = useToast();
+  const scrollRef = useRef<HTMLDivElement>(null);
+
+  // Add generation popover state
+  const [searchQuery, setSearchQuery] = useState('');
+  const [isAddOpen, setIsAddOpen] = useState(false);
+  const { data: historyData } = useHistory();
+
+  // Filter generations not in story and matching search
+  const availableGenerations = useMemo(() => {
+    if (!historyData?.items || !story) return [];
+    const storyGenerationIds = new Set(story.items.map((i) => i.generation_id));
+    const query = searchQuery.toLowerCase();
+    return historyData.items.filter(
+      (gen) =>
+        !storyGenerationIds.has(gen.id) &&
+        (gen.text.toLowerCase().includes(query) ||
+          gen.profile_name.toLowerCase().includes(query)),
+    );
+  }, [historyData, story, searchQuery]);
+
+  // Get track editor height from store for dynamic padding
+  const trackEditorHeight = useStoryStore((state) => state.trackEditorHeight);
+
+  // Track editor is shown when story has items
+  const hasBottomBar = story && story.items.length > 0;
+
+  // Calculate dynamic bottom padding: track editor + gap
+  const bottomPadding = hasBottomBar ? trackEditorHeight + 24 : 0;
+
+  // Drag and drop sensors
+  const sensors = useSensors(
+    useSensor(PointerSensor, {
+      activationConstraint: {
+        distance: 8,
+      },
+    }),
+    useSensor(KeyboardSensor, {
+      coordinateGetter: sortableKeyboardCoordinates,
+    }),
+  );
+
+  // Playback state (for auto-scroll and item highlighting)
+  const isPlaying = useStoryStore((state) => state.isPlaying);
+  const currentTimeMs = useStoryStore((state) => state.currentTimeMs);
+  const playbackStoryId = useStoryStore((state) => state.playbackStoryId);
+
+  // Refs for auto-scrolling to playing item
+  const itemRefsMap = useRef<Map<string, HTMLDivElement>>(new Map());
+  const lastScrolledItemRef = useRef<string | null>(null);
+
+  // Use playback hook
+  useStoryPlayback(story?.items);
+
+  // Sort items by start_time_ms
+  const sortedItems = useMemo(() => {
+    if (!story?.items) return [];
+    return [...story.items].sort((a, b) => a.start_time_ms - b.start_time_ms);
+  }, [story?.items]);
+
+  // Find the currently playing item based on timecode
+  const currentlyPlayingItemId = useMemo(() => {
+    if (!isPlaying || playbackStoryId !== story?.id || !sortedItems.length) {
+      return null;
+    }
+    const playingItem = sortedItems.find((item) => {
+      const itemStart = item.start_time_ms;
+      const itemEnd = item.start_time_ms + item.duration * 1000;
+      return currentTimeMs >= itemStart && currentTimeMs < itemEnd;
+    });
+    return playingItem?.generation_id ?? null;
+  }, [isPlaying, playbackStoryId, story?.id, sortedItems, currentTimeMs]);
+
+  // Auto-scroll to the currently playing item
+  useEffect(() => {
+    if (!currentlyPlayingItemId || currentlyPlayingItemId === lastScrolledItemRef.current) {
+      return;
+    }
+
+    const element = itemRefsMap.current.get(currentlyPlayingItemId);
+    if (element && scrollRef.current) {
+      element.scrollIntoView({ behavior: 'smooth', block: 'start' });
+      lastScrolledItemRef.current = currentlyPlayingItemId;
+    }
+  }, [currentlyPlayingItemId]);
+
+  // Reset last scrolled item when playback stops
+  useEffect(() => {
+    if (!isPlaying) {
+      lastScrolledItemRef.current = null;
+    }
+  }, [isPlaying]);
+
+  const handleRemoveItem = (itemId: string) => {
+    if (!story) return;
+
+    removeItem.mutate(
+      {
+        storyId: story.id,
+        itemId,
+      },
+      {
+        onError: (error) => {
+          toast({
+            title: 'Failed to remove item',
+            description: error.message,
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  };
+
+  const handleDragEnd = (event: DragEndEvent) => {
+    const { active, over } = event;
+
+    if (!story || !over || active.id === over.id) return;
+
+    const oldIndex = sortedItems.findIndex((item) => item.generation_id === active.id);
+    const newIndex = sortedItems.findIndex((item) => item.generation_id === over.id);
+
+    if (oldIndex === -1 || newIndex === -1) return;
+
+    // Calculate the new order
+    const newOrder = arrayMove(sortedItems, oldIndex, newIndex);
+    const generationIds = newOrder.map((item) => item.generation_id);
+
+    // Send reorder request to backend
+    reorderItems.mutate(
+      {
+        storyId: story.id,
+        data: { generation_ids: generationIds },
+      },
+      {
+        onError: (error) => {
+          toast({
+            title: 'Failed to reorder items',
+            description: error.message,
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  };
+
+  const handleExportAudio = () => {
+    if (!story) return;
+
+    exportAudio.mutate(
+      {
+        storyId: story.id,
+        storyName: story.name,
+      },
+      {
+        onError: (error) => {
+          toast({
+            title: 'Failed to export audio',
+            description: error.message,
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  };
+
+  const handleAddGeneration = (generationId: string) => {
+    if (!story) return;
+
+    addStoryItem.mutate(
+      {
+        storyId: story.id,
+        data: { generation_id: generationId },
+      },
+      {
+        onSuccess: () => {
+          setIsAddOpen(false);
+          setSearchQuery('');
+        },
+        onError: (error) => {
+          toast({
+            title: 'Failed to add generation',
+            description: error.message,
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  };
+
+  if (!selectedStoryId) {
+    return (
+      <div className="flex items-center justify-center h-full text-muted-foreground">
+        <div className="text-center">
+          <p className="text-lg font-medium mb-2">Select a story</p>
+          <p className="text-sm">Choose a story from the list to view its content</p>
+        </div>
+      </div>
+    );
+  }
+
+  if (isLoading) {
+    return (
+      <div className="flex items-center justify-center h-full">
+        <div className="text-muted-foreground">Loading story...</div>
+      </div>
+    );
+  }
+
+  if (!story) {
+    return (
+      <div className="flex items-center justify-center h-full text-muted-foreground">
+        <div className="text-center">
+          <p className="text-lg font-medium mb-2">Story not found</p>
+          <p className="text-sm">The selected story could not be loaded</p>
+        </div>
+      </div>
+    );
+  }
+
+  return (
+    <div className="flex flex-col h-full min-h-0">
+      {/* Header */}
+      <div className="flex items-center justify-between mb-4 px-1">
+        <div>
+          <h2 className="text-2xl font-bold">{story.name}</h2>
+          {story.description && (
+            <p className="text-sm text-muted-foreground mt-1">{story.description}</p>
+          )}
+        </div>
+        <div className="flex gap-2">
+          <Popover open={isAddOpen} onOpenChange={setIsAddOpen}>
+            <PopoverTrigger asChild>
+              <Button variant="outline" size="sm">
+                <Plus className="mr-2 h-4 w-4" />
+                Add
+              </Button>
+            </PopoverTrigger>
+            <PopoverContent className="w-80 p-0" align="end">
+              <div className="p-2 border-b">
+                <Input
+                  placeholder="Search by name or transcript..."
+                  value={searchQuery}
+                  onChange={(e) => setSearchQuery(e.target.value)}
+                  autoFocus
+                />
+              </div>
+              <div className="max-h-60 overflow-y-auto">
+                {availableGenerations.length === 0 ? (
+                  <div className="p-4 text-center text-sm text-muted-foreground">
+                    {searchQuery
+                      ? 'No matching generations found'
+                      : 'No available generations'}
+                  </div>
+                ) : (
+                  availableGenerations.map((gen) => (
+                    <button
+                      key={gen.id}
+                      type="button"
+                      className="w-full text-left px-3 py-2 hover:bg-muted transition-colors border-b last:border-b-0"
+                      onClick={() => handleAddGeneration(gen.id)}
+                    >
+                      <div className="font-medium text-sm">{gen.profile_name}</div>
+                      <div className="text-xs text-muted-foreground truncate">
+                        {gen.text.length > 50 ? `${gen.text.substring(0, 50)}...` : gen.text}
+                      </div>
+                    </button>
+                  ))
+                )}
+              </div>
+            </PopoverContent>
+          </Popover>
+          {story.items.length > 0 && (
+            <Button
+              variant="outline"
+              size="sm"
+              onClick={handleExportAudio}
+              disabled={exportAudio.isPending}
+            >
+              <Download className="mr-2 h-4 w-4" />
+              Export Audio
+            </Button>
+          )}
+        </div>
+      </div>
+
+      {/* Content */}
+      <div
+        ref={scrollRef}
+        className="flex-1 min-h-0 overflow-y-auto space-y-3"
+        style={{ paddingBottom: bottomPadding > 0 ? `${bottomPadding}px` : undefined }}
+      >
+        {sortedItems.length === 0 ? (
+          <div className="text-center py-12 px-5 border-2 border-dashed border-muted rounded-md text-muted-foreground">
+            <p className="text-sm">No items in this story</p>
+            <p className="text-xs mt-2">Generate speech using the box below to add items</p>
+          </div>
+        ) : (
+          <DndContext
+            sensors={sensors}
+            collisionDetection={closestCenter}
+            onDragEnd={handleDragEnd}
+          >
+            <SortableContext
+              items={sortedItems.map((item) => item.generation_id)}
+              strategy={verticalListSortingStrategy}
+            >
+              <div className="space-y-3">
+                {sortedItems.map((item, index) => (
+                  <div
+                    key={item.id}
+                    ref={(el) => {
+                      if (el) {
+                        itemRefsMap.current.set(item.generation_id, el);
+                      } else {
+                        itemRefsMap.current.delete(item.generation_id);
+                      }
+                    }}
+                  >
+                    <SortableStoryChatItem
+                      item={item}
+                      storyId={story.id}
+                      index={index}
+                      onRemove={() => handleRemoveItem(item.id)}
+                      currentTimeMs={currentTimeMs}
+                      isPlaying={isPlaying && playbackStoryId === story.id}
+                    />
+                  </div>
+                ))}
+              </div>
+            </SortableContext>
+          </DndContext>
+        )}
+      </div>
+    </div>
+  );
+}

app/src/components/StoriesTab/StoryList.tsx

@@ -0,0 +1,369 @@
+import { Plus, BookOpen, MoreHorizontal, Pencil, Trash2 } from 'lucide-react';
+import { useState } from 'react';
+import {
+  AlertDialog,
+  AlertDialogAction,
+  AlertDialogCancel,
+  AlertDialogContent,
+  AlertDialogDescription,
+  AlertDialogFooter,
+  AlertDialogHeader,
+  AlertDialogTitle,
+} from '@/components/ui/alert-dialog';
+import { Button } from '@/components/ui/button';
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from '@/components/ui/dialog';
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuTrigger,
+} from '@/components/ui/dropdown-menu';
+import { Input } from '@/components/ui/input';
+import { Label } from '@/components/ui/label';
+import { Textarea } from '@/components/ui/textarea';
+import { useToast } from '@/components/ui/use-toast';
+import { useStories, useCreateStory, useUpdateStory, useDeleteStory } from '@/lib/hooks/useStories';
+import { cn } from '@/lib/utils/cn';
+import { formatDate } from '@/lib/utils/format';
+import { useStoryStore } from '@/stores/storyStore';
+
+export function StoryList() {
+  const { data: stories, isLoading } = useStories();
+  const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
+  const setSelectedStoryId = useStoryStore((state) => state.setSelectedStoryId);
+  const createStory = useCreateStory();
+  const updateStory = useUpdateStory();
+  const deleteStory = useDeleteStory();
+  const [createDialogOpen, setCreateDialogOpen] = useState(false);
+  const [editDialogOpen, setEditDialogOpen] = useState(false);
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [editingStory, setEditingStory] = useState<{
+    id: string;
+    name: string;
+    description?: string;
+  } | null>(null);
+  const [deletingStoryId, setDeletingStoryId] = useState<string | null>(null);
+  const [newStoryName, setNewStoryName] = useState('');
+  const [newStoryDescription, setNewStoryDescription] = useState('');
+  const { toast } = useToast();
+
+  const handleCreateStory = () => {
+    if (!newStoryName.trim()) {
+      toast({
+        title: 'Name required',
+        description: 'Please enter a story name',
+        variant: 'destructive',
+      });
+      return;
+    }
+
+    createStory.mutate(
+      {
+        name: newStoryName.trim(),
+        description: newStoryDescription.trim() || undefined,
+      },
+      {
+        onSuccess: (story) => {
+          setSelectedStoryId(story.id);
+          setCreateDialogOpen(false);
+          setNewStoryName('');
+          setNewStoryDescription('');
+          toast({
+            title: 'Story created',
+            description: `"${story.name}" has been created`,
+          });
+        },
+        onError: (error) => {
+          toast({
+            title: 'Failed to create story',
+            description: error.message,
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  };
+
+  const handleEditClick = (story: { id: string; name: string; description?: string }) => {
+    setEditingStory(story);
+    setNewStoryName(story.name);
+    setNewStoryDescription(story.description || '');
+    setEditDialogOpen(true);
+  };
+
+  const handleUpdateStory = () => {
+    if (!editingStory || !newStoryName.trim()) {
+      toast({
+        title: 'Name required',
+        description: 'Please enter a story name',
+        variant: 'destructive',
+      });
+      return;
+    }
+
+    updateStory.mutate(
+      {
+        storyId: editingStory.id,
+        data: {
+          name: newStoryName.trim(),
+          description: newStoryDescription.trim() || undefined,
+        },
+      },
+      {
+        onSuccess: () => {
+          setEditDialogOpen(false);
+          setEditingStory(null);
+          setNewStoryName('');
+          setNewStoryDescription('');
+        },
+        onError: (error) => {
+          toast({
+            title: 'Failed to update story',
+            description: error.message,
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  };
+
+  const handleDeleteClick = (storyId: string) => {
+    setDeletingStoryId(storyId);
+    setDeleteDialogOpen(true);
+  };
+
+  const handleDeleteConfirm = () => {
+    if (!deletingStoryId) return;
+
+    deleteStory.mutate(deletingStoryId, {
+      onSuccess: () => {
+        // Clear selection if deleting the currently selected story
+        if (selectedStoryId === deletingStoryId) {
+          setSelectedStoryId(null);
+        }
+        setDeleteDialogOpen(false);
+        setDeletingStoryId(null);
+      },
+      onError: (error) => {
+        toast({
+          title: 'Failed to delete story',
+          description: error.message,
+          variant: 'destructive',
+        });
+      },
+    });
+  };
+
+  if (isLoading) {
+    return (
+      <div className="flex items-center justify-center h-full">
+        <div className="text-muted-foreground">Loading stories...</div>
+      </div>
+    );
+  }
+
+  const storyList = stories || [];
+
+  return (
+    <div className="flex flex-col h-full min-h-0">
+      {/* Header */}
+      <div className="flex items-center justify-between mb-4 px-1">
+        <h2 className="text-2xl font-bold">Stories</h2>
+        <Button onClick={() => setCreateDialogOpen(true)} size="sm">
+          <Plus className="mr-2 h-4 w-4" />
+          New Story
+        </Button>
+      </div>
+
+      {/* Story List */}
+      <div className="flex-1 min-h-0 overflow-y-auto space-y-2">
+        {storyList.length === 0 ? (
+          <div className="text-center py-12 px-5 border-2 border-dashed border-muted rounded-2xl text-muted-foreground">
+            <BookOpen className="h-12 w-12 mx-auto mb-4 opacity-50" />
+            <p className="text-sm">No stories yet</p>
+            <p className="text-xs mt-2">Create your first story to get started</p>
+          </div>
+        ) : (
+          storyList.map((story) => (
+            <div
+              key={story.id}
+              className={cn(
+                'h-24 p-4 border rounded-2xl transition-colors group flex items-center',
+                selectedStoryId === story.id && 'bg-muted border-primary',
+              )}
+            >
+              <div className="flex items-start justify-between gap-2 w-full min-w-0">
+                <button
+                  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">
+                      {story.description}
+                    </p>
+                  )}
+                  <div className="flex items-center gap-3 mt-2 text-xs text-muted-foreground">
+                    <span>
+                      {story.item_count} {story.item_count === 1 ? 'item' : 'items'}
+                    </span>
+                    <span>•</span>
+                    <span>{formatDate(story.updated_at)}</span>
+                  </div>
+                </button>
+                <DropdownMenu>
+                  <DropdownMenuTrigger asChild>
+                    <Button
+                      variant="ghost"
+                      size="icon"
+                      className="h-8 w-8 opacity-0 group-hover:opacity-100 transition-opacity"
+                      onClick={(e) => e.stopPropagation()}
+                    >
+                      <MoreHorizontal className="h-4 w-4" />
+                    </Button>
+                  </DropdownMenuTrigger>
+                  <DropdownMenuContent align="end">
+                    <DropdownMenuItem onClick={() => handleEditClick(story)}>
+                      <Pencil className="mr-2 h-4 w-4" />
+                      Edit
+                    </DropdownMenuItem>
+                    <DropdownMenuItem
+                      onClick={() => handleDeleteClick(story.id)}
+                      className="text-destructive focus:text-destructive"
+                    >
+                      <Trash2 className="mr-2 h-4 w-4" />
+                      Delete
+                    </DropdownMenuItem>
+                  </DropdownMenuContent>
+                </DropdownMenu>
+              </div>
+            </div>
+          ))
+        )}
+      </div>
+
+      {/* Create Story Dialog */}
+      <Dialog open={createDialogOpen} onOpenChange={setCreateDialogOpen}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>Create New Story</DialogTitle>
+            <DialogDescription>
+              Create a new story to organize your voice generations into conversations.
+            </DialogDescription>
+          </DialogHeader>
+          <div className="space-y-4 py-4">
+            <div className="space-y-2">
+              <Label htmlFor="story-name">Name</Label>
+              <Input
+                id="story-name"
+                placeholder="My Story"
+                value={newStoryName}
+                onChange={(e) => setNewStoryName(e.target.value)}
+                onKeyDown={(e) => {
+                  if (e.key === 'Enter') {
+                    handleCreateStory();
+                  }
+                }}
+              />
+            </div>
+            <div className="space-y-2">
+              <Label htmlFor="story-description">Description (optional)</Label>
+              <Textarea
+                id="story-description"
+                placeholder="A conversation between..."
+                value={newStoryDescription}
+                onChange={(e) => setNewStoryDescription(e.target.value)}
+                rows={3}
+              />
+            </div>
+          </div>
+          <DialogFooter>
+            <Button variant="outline" onClick={() => setCreateDialogOpen(false)}>
+              Cancel
+            </Button>
+            <Button onClick={handleCreateStory} disabled={createStory.isPending}>
+              {createStory.isPending ? 'Creating...' : 'Create'}
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+
+      {/* Edit Story Dialog */}
+      <Dialog open={editDialogOpen} onOpenChange={setEditDialogOpen}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>Edit Story</DialogTitle>
+            <DialogDescription>Update the story name and description.</DialogDescription>
+          </DialogHeader>
+          <div className="space-y-4 py-4">
+            <div className="space-y-2">
+              <Label htmlFor="edit-story-name">Name</Label>
+              <Input
+                id="edit-story-name"
+                placeholder="My Story"
+                value={newStoryName}
+                onChange={(e) => setNewStoryName(e.target.value)}
+                onKeyDown={(e) => {
+                  if (e.key === 'Enter') {
+                    handleUpdateStory();
+                  }
+                }}
+              />
+            </div>
+            <div className="space-y-2">
+              <Label htmlFor="edit-story-description">Description (optional)</Label>
+              <Textarea
+                id="edit-story-description"
+                placeholder="A conversation between..."
+                value={newStoryDescription}
+                onChange={(e) => setNewStoryDescription(e.target.value)}
+                rows={3}
+              />
+            </div>
+          </div>
+          <DialogFooter>
+            <Button variant="outline" onClick={() => setEditDialogOpen(false)}>
+              Cancel
+            </Button>
+            <Button onClick={handleUpdateStory} disabled={updateStory.isPending}>
+              {updateStory.isPending ? 'Saving...' : 'Save'}
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+
+      {/* Delete Story Confirmation Dialog */}
+      <AlertDialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>Are you sure?</AlertDialogTitle>
+            <AlertDialogDescription>
+              This will permanently delete the story and all its items. This action cannot be
+              undone.
+            </AlertDialogDescription>
+          </AlertDialogHeader>
+          <AlertDialogFooter>
+            <AlertDialogCancel>Cancel</AlertDialogCancel>
+            <AlertDialogAction asChild>
+              <Button
+                onClick={handleDeleteConfirm}
+                disabled={deleteStory.isPending}
+                className="bg-destructive text-destructive-foreground hover:bg-destructive/90"
+              >
+                {deleteStory.isPending ? 'Deleting...' : 'Delete'}
+              </Button>
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
+    </div>
+  );
+}

app/src/components/StoriesTab/StoryTrackEditor.tsx

@@ -0,0 +1,988 @@
+import {
+  Copy,
+  GripHorizontal,
+  Minus,
+  Pause,
+  Play,
+  Plus,
+  Scissors,
+  Square,
+  Trash2,
+} from 'lucide-react';
+import { useCallback, useEffect, useMemo, useRef, useState } from 'react';
+import WaveSurfer from 'wavesurfer.js';
+import { Button } from '@/components/ui/button';
+import { useToast } from '@/components/ui/use-toast';
+import { apiClient } from '@/lib/api/client';
+import type { StoryItemDetail } from '@/lib/api/types';
+import {
+  useDuplicateStoryItem,
+  useMoveStoryItem,
+  useRemoveStoryItem,
+  useSplitStoryItem,
+  useTrimStoryItem,
+} from '@/lib/hooks/useStories';
+import { cn } from '@/lib/utils/cn';
+import { useStoryStore } from '@/stores/storyStore';
+
+// Clip waveform component with trim support
+function ClipWaveform({
+  generationId,
+  width,
+  trimStartMs,
+  trimEndMs,
+  duration,
+}: {
+  generationId: string;
+  width: number;
+  trimStartMs: number;
+  trimEndMs: number;
+  duration: number;
+}) {
+  const waveformRef = useRef<HTMLDivElement>(null);
+  const wavesurferRef = useRef<WaveSurfer | null>(null);
+
+  // Calculate the full waveform width based on the original duration
+  // The visible portion (width) represents the effective duration after trimming
+  const effectiveDurationMs = duration * 1000 - trimStartMs - trimEndMs;
+  const fullWaveformWidth =
+    effectiveDurationMs > 0 ? (width / effectiveDurationMs) * (duration * 1000) : width;
+
+  // Calculate how much to offset the waveform to hide the trimmed start
+  const offsetX =
+    effectiveDurationMs > 0 ? (trimStartMs / (duration * 1000)) * fullWaveformWidth : 0;
+
+  useEffect(() => {
+    if (!waveformRef.current || fullWaveformWidth < 20) return;
+
+    // Get CSS colors
+    const root = document.documentElement;
+    const getCSSVar = (varName: string) => {
+      const value = getComputedStyle(root).getPropertyValue(varName).trim();
+      return value ? `hsl(${value})` : '';
+    };
+
+    const waveColor = getCSSVar('--accent-foreground');
+
+    const wavesurfer = WaveSurfer.create({
+      container: waveformRef.current,
+      waveColor,
+      progressColor: waveColor,
+      cursorWidth: 0,
+      barWidth: 1,
+      barRadius: 1,
+      barGap: 1,
+      height: 28,
+      normalize: true,
+      interact: false,
+    });
+
+    wavesurferRef.current = wavesurfer;
+
+    const audioUrl = apiClient.getAudioUrl(generationId);
+    wavesurfer.load(audioUrl).catch(() => {
+      // Ignore load errors
+    });
+
+    return () => {
+      wavesurfer.destroy();
+      wavesurferRef.current = null;
+    };
+  }, [generationId, fullWaveformWidth]);
+
+  return (
+    <div className="w-full h-full opacity-60 overflow-hidden">
+      {/* Inner container that holds the full waveform, offset to show only visible portion */}
+      <div
+        ref={waveformRef}
+        style={{
+          width: `${fullWaveformWidth}px`,
+          transform: `translateX(-${offsetX}px)`,
+        }}
+        className="h-full"
+      />
+    </div>
+  );
+}
+
+interface StoryTrackEditorProps {
+  storyId: string;
+  items: StoryItemDetail[];
+}
+
+const TRACK_HEIGHT = 48;
+const TIME_RULER_HEIGHT = 24; // h-6 = 1.5rem = 24px
+const MIN_PIXELS_PER_SECOND = 10;
+const MAX_PIXELS_PER_SECOND = 200;
+const DEFAULT_PIXELS_PER_SECOND = 50;
+const DEFAULT_TRACKS = [1, 0, -1]; // Default 3 tracks
+const MIN_EDITOR_HEIGHT = 120;
+const MAX_EDITOR_HEIGHT = 500;
+
+export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
+  const [pixelsPerSecond, setPixelsPerSecond] = useState(DEFAULT_PIXELS_PER_SECOND);
+  const [draggingItem, setDraggingItem] = useState<string | null>(null);
+  const [dragOffset, setDragOffset] = useState({ x: 0, y: 0 });
+  const [dragPosition, setDragPosition] = useState({ x: 0, y: 0 });
+  const [isResizing, setIsResizing] = useState(false);
+  const [containerWidth, setContainerWidth] = useState(0);
+  const containerRef = useRef<HTMLDivElement>(null);
+  const tracksRef = useRef<HTMLDivElement>(null);
+  const resizeStartY = useRef(0);
+  const resizeStartHeight = useRef(0);
+  const moveItem = useMoveStoryItem();
+  const trimItem = useTrimStoryItem();
+  const splitItem = useSplitStoryItem();
+  const duplicateItem = useDuplicateStoryItem();
+  const removeItem = useRemoveStoryItem();
+  const { toast } = useToast();
+
+  // Selection state
+  const selectedClipId = useStoryStore((state) => state.selectedClipId);
+  const setSelectedClipId = useStoryStore((state) => state.setSelectedClipId);
+
+  // Trim state
+  const [trimmingItem, setTrimmingItem] = useState<string | null>(null);
+  const [trimSide, setTrimSide] = useState<'start' | 'end' | null>(null);
+  const [trimStartX, setTrimStartX] = useState(0);
+  const [tempTrimValues, setTempTrimValues] = useState<{
+    trim_start_ms: number;
+    trim_end_ms: number;
+  } | null>(null);
+
+  // Track editor height from store (shared with FloatingGenerateBox)
+  const editorHeight = useStoryStore((state) => state.trackEditorHeight);
+  const setEditorHeight = useStoryStore((state) => state.setTrackEditorHeight);
+
+  // Playback state
+  const isPlaying = useStoryStore((state) => state.isPlaying);
+  const currentTimeMs = useStoryStore((state) => state.currentTimeMs);
+  const playbackStoryId = useStoryStore((state) => state.playbackStoryId);
+  const play = useStoryStore((state) => state.play);
+  const pause = useStoryStore((state) => state.pause);
+  const stop = useStoryStore((state) => state.stop);
+  const seek = useStoryStore((state) => state.seek);
+  const setActiveStory = useStoryStore((state) => state.setActiveStory);
+
+  const isActiveStory = playbackStoryId === storyId;
+  const isCurrentlyPlaying = isPlaying && isActiveStory;
+
+  // Auto-activate this story when the editor is shown so playhead is visible
+  useEffect(() => {
+    if (items.length > 0 && !isActiveStory) {
+      const totalDuration = Math.max(
+        ...items.map((item) => {
+          const trimStart = item.trim_start_ms || 0;
+          const trimEnd = item.trim_end_ms || 0;
+          const effectiveDuration = item.duration * 1000 - trimStart - trimEnd;
+          return item.start_time_ms + effectiveDuration;
+        }),
+        0,
+      );
+      setActiveStory(storyId, items, totalDuration);
+    }
+  }, [storyId, items, isActiveStory, setActiveStory]);
+
+  // Sort items by start time for play
+  const sortedItems = useMemo(() => {
+    return [...items].sort((a, b) => a.start_time_ms - b.start_time_ms);
+  }, [items]);
+
+  const handlePlayPause = () => {
+    if (isCurrentlyPlaying) {
+      pause();
+    } else {
+      play(storyId, sortedItems);
+    }
+  };
+
+  const handleStop = () => {
+    stop();
+  };
+
+  // Calculate unique tracks from items, always showing at least 3 default tracks
+  const tracks = useMemo(() => {
+    const trackSet = new Set([...DEFAULT_TRACKS, ...items.map((item) => item.track)]);
+    return Array.from(trackSet).sort((a, b) => b - a); // Higher tracks on top
+  }, [items]);
+
+  // Track container width for full-width minimum
+  useEffect(() => {
+    const container = tracksRef.current;
+    if (!container) return;
+
+    const observer = new ResizeObserver((entries) => {
+      for (const entry of entries) {
+        setContainerWidth(entry.contentRect.width);
+      }
+    });
+
+    observer.observe(container);
+    // Set initial width
+    setContainerWidth(container.clientWidth);
+
+    return () => observer.disconnect();
+  }, []);
+
+  // Calculate effective duration (accounting for trims)
+  const getEffectiveDuration = (item: StoryItemDetail) => {
+    return item.duration * 1000 - (item.trim_start_ms || 0) - (item.trim_end_ms || 0);
+  };
+
+  // Calculate total duration (using effective durations)
+  const totalDurationMs = useMemo(() => {
+    if (items.length === 0) return 10000; // Default 10 seconds
+    return Math.max(...items.map((item) => item.start_time_ms + getEffectiveDuration(item)), 10000);
+  }, [items, getEffectiveDuration]);
+
+  // Calculate timeline width - at least full container width
+  const contentWidth = (totalDurationMs / 1000) * pixelsPerSecond + 200; // Content width with padding
+  const timelineWidth = Math.max(contentWidth, containerWidth);
+
+  // Generate time markers
+  const timeMarkers = useMemo(() => {
+    const markers: number[] = [];
+    // Determine interval based on zoom level
+    let intervalMs = 5000; // 5 seconds
+    if (pixelsPerSecond > 100) intervalMs = 1000;
+    else if (pixelsPerSecond > 50) intervalMs = 2000;
+    else if (pixelsPerSecond < 20) intervalMs = 10000;
+
+    for (let ms = 0; ms <= totalDurationMs + intervalMs; ms += intervalMs) {
+      markers.push(ms);
+    }
+    return markers;
+  }, [totalDurationMs, pixelsPerSecond]);
+
+  const formatTime = (ms: number): string => {
+    const totalSeconds = Math.floor(ms / 1000);
+    const minutes = Math.floor(totalSeconds / 60);
+    const seconds = totalSeconds % 60;
+    return `${minutes}:${seconds.toString().padStart(2, '0')}`;
+  };
+
+  const msToPixels = useCallback((ms: number) => (ms / 1000) * pixelsPerSecond, [pixelsPerSecond]);
+
+  const pixelsToMs = useCallback((px: number) => (px / pixelsPerSecond) * 1000, [pixelsPerSecond]);
+
+  const handleZoomIn = () => {
+    setPixelsPerSecond((prev) => Math.min(prev * 1.5, MAX_PIXELS_PER_SECOND));
+  };
+
+  const handleZoomOut = () => {
+    setPixelsPerSecond((prev) => Math.max(prev / 1.5, MIN_PIXELS_PER_SECOND));
+  };
+
+  // Resize handlers
+  const handleResizeStart = useCallback(
+    (e: React.MouseEvent) => {
+      e.preventDefault();
+      setIsResizing(true);
+      resizeStartY.current = e.clientY;
+      resizeStartHeight.current = editorHeight;
+    },
+    [editorHeight],
+  );
+
+  const handleResizeMove = useCallback(
+    (e: MouseEvent) => {
+      if (!isResizing) return;
+      const deltaY = resizeStartY.current - e.clientY;
+      const newHeight = Math.min(
+        MAX_EDITOR_HEIGHT,
+        Math.max(MIN_EDITOR_HEIGHT, resizeStartHeight.current + deltaY),
+      );
+      setEditorHeight(newHeight);
+    },
+    [isResizing, setEditorHeight],
+  );
+
+  const handleResizeEnd = useCallback(() => {
+    setIsResizing(false);
+  }, []);
+
+  // Add global mouse listeners for resizing
+  useEffect(() => {
+    if (isResizing) {
+      window.addEventListener('mousemove', handleResizeMove);
+      window.addEventListener('mouseup', handleResizeEnd);
+      return () => {
+        window.removeEventListener('mousemove', handleResizeMove);
+        window.removeEventListener('mouseup', handleResizeEnd);
+      };
+    }
+  }, [isResizing, handleResizeMove, handleResizeEnd]);
+
+  const handleTimelineClick = (e: React.MouseEvent<HTMLDivElement>) => {
+    if (!tracksRef.current || draggingItem || trimmingItem) return;
+    const rect = tracksRef.current.getBoundingClientRect();
+    const x = e.clientX - rect.left + tracksRef.current.scrollLeft;
+    const timeMs = Math.max(0, pixelsToMs(x));
+    seek(timeMs);
+    // Deselect clip when clicking on timeline
+    setSelectedClipId(null);
+  };
+
+  const handleClipClick = (e: React.MouseEvent, item: StoryItemDetail) => {
+    e.stopPropagation();
+    if (draggingItem || trimmingItem) return;
+    setSelectedClipId(item.id);
+  };
+
+  const handleTrimStart = (e: React.MouseEvent, item: StoryItemDetail, side: 'start' | 'end') => {
+    e.stopPropagation();
+    if (!tracksRef.current) return;
+    setTrimmingItem(item.id);
+    setTrimSide(side);
+    setSelectedClipId(item.id);
+    setTrimStartX(e.clientX);
+    trimStartItemRef.current = {
+      item,
+      initialTrimStart: item.trim_start_ms || 0,
+      initialTrimEnd: item.trim_end_ms || 0,
+    };
+  };
+
+  const trimStartItemRef = useRef<{
+    item: StoryItemDetail;
+    initialTrimStart: number;
+    initialTrimEnd: number;
+  } | null>(null);
+
+  const handleTrimMove = useCallback(
+    (e: MouseEvent) => {
+      if (!trimmingItem || !trimSide || !trimStartItemRef.current) return;
+
+      const deltaX = e.clientX - trimStartX;
+      const deltaMs = pixelsToMs(deltaX); // Signed delta in milliseconds
+
+      const { item, initialTrimStart, initialTrimEnd } = trimStartItemRef.current;
+      const originalDurationMs = item.duration * 1000;
+
+      let newTrimStart = initialTrimStart;
+      let newTrimEnd = initialTrimEnd;
+
+      if (trimSide === 'start') {
+        // Moving right increases trim_start (trims more from start)
+        // Moving left decreases trim_start (restores from start)
+        newTrimStart = Math.round(
+          Math.max(
+            0,
+            Math.min(initialTrimStart + deltaMs, originalDurationMs - initialTrimEnd - 100),
+          ),
+        );
+      } else {
+        // Moving right decreases trim_end (restores from end)
+        // Moving left increases trim_end (trims more from end)
+        newTrimEnd = Math.round(
+          Math.max(
+            0,
+            Math.min(initialTrimEnd - deltaMs, originalDurationMs - initialTrimStart - 100),
+          ),
+        );
+      }
+
+      // Validate that we don't exceed duration
+      if (newTrimStart + newTrimEnd >= originalDurationMs - 100) {
+        return; // Don't allow trimming to less than 100ms
+      }
+
+      // Update temporary trim values for visual feedback
+      setTempTrimValues({
+        trim_start_ms: newTrimStart,
+        trim_end_ms: newTrimEnd,
+      });
+    },
+    [trimmingItem, trimSide, trimStartX, pixelsToMs],
+  );
+
+  const handleTrimEnd = useCallback(() => {
+    if (!trimmingItem || !trimSide || !trimStartItemRef.current) {
+      setTrimmingItem(null);
+      setTrimSide(null);
+      setTempTrimValues(null);
+      trimStartItemRef.current = null;
+      return;
+    }
+
+    const { initialTrimStart, initialTrimEnd } = trimStartItemRef.current;
+
+    // Use temporary trim values if available, otherwise use initial values
+    // Ensure values are integers for the backend
+    const finalTrimStart = Math.round(tempTrimValues?.trim_start_ms ?? initialTrimStart);
+    const finalTrimEnd = Math.round(tempTrimValues?.trim_end_ms ?? initialTrimEnd);
+
+    // Only update if values changed
+    if (finalTrimStart !== initialTrimStart || finalTrimEnd !== initialTrimEnd) {
+      trimItem.mutate(
+        {
+          storyId,
+          itemId: trimmingItem,
+          data: {
+            trim_start_ms: finalTrimStart,
+            trim_end_ms: finalTrimEnd,
+          },
+        },
+        {
+          onError: (error) => {
+            toast({
+              title: 'Failed to trim clip',
+              description: error instanceof Error ? error.message : String(error),
+              variant: 'destructive',
+            });
+          },
+        },
+      );
+    }
+
+    setTrimmingItem(null);
+    setTrimSide(null);
+    setTempTrimValues(null);
+    trimStartItemRef.current = null;
+  }, [trimmingItem, trimSide, tempTrimValues, storyId, trimItem, toast]);
+
+  const handleSplit = useCallback(() => {
+    if (!selectedClipId) return;
+
+    const item = items.find((i) => i.id === selectedClipId);
+    if (!item) return;
+
+    const splitTimeMs = currentTimeMs - item.start_time_ms;
+    const effectiveDuration = getEffectiveDuration(item);
+
+    if (splitTimeMs <= 0 || splitTimeMs >= effectiveDuration) {
+      toast({
+        title: 'Invalid split point',
+        description: 'Playhead must be within the selected clip',
+        variant: 'destructive',
+      });
+      return;
+    }
+
+    splitItem.mutate(
+      {
+        storyId,
+        itemId: selectedClipId,
+        data: { split_time_ms: splitTimeMs },
+      },
+      {
+        onSuccess: () => {
+          setSelectedClipId(null);
+        },
+        onError: (error) => {
+          toast({
+            title: 'Failed to split clip',
+            description: error instanceof Error ? error.message : String(error),
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  }, [
+    selectedClipId,
+    items,
+    currentTimeMs,
+    getEffectiveDuration,
+    storyId,
+    splitItem,
+    toast,
+    setSelectedClipId,
+  ]);
+
+  const handleDuplicate = useCallback(() => {
+    if (!selectedClipId) return;
+
+    duplicateItem.mutate(
+      {
+        storyId,
+        itemId: selectedClipId,
+      },
+      {
+        onError: (error) => {
+          toast({
+            title: 'Failed to duplicate clip',
+            description: error instanceof Error ? error.message : String(error),
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  }, [selectedClipId, storyId, duplicateItem, toast]);
+
+  const handleDelete = useCallback(() => {
+    if (!selectedClipId) return;
+
+    removeItem.mutate(
+      {
+        storyId,
+        itemId: selectedClipId,
+      },
+      {
+        onSuccess: () => {
+          setSelectedClipId(null);
+        },
+        onError: (error) => {
+          toast({
+            title: 'Failed to delete clip',
+            description: error instanceof Error ? error.message : String(error),
+            variant: 'destructive',
+          });
+        },
+      },
+    );
+  }, [selectedClipId, storyId, removeItem, toast, setSelectedClipId]);
+
+  // Keyboard shortcuts
+  useEffect(() => {
+    const handleKeyDown = (e: KeyboardEvent) => {
+      // Only handle shortcuts when editor is focused or no input is focused
+      if (e.target instanceof HTMLInputElement || e.target instanceof HTMLTextAreaElement) {
+        return;
+      }
+
+      if (e.key === ' ') {
+        e.preventDefault();
+        handlePlayPause();
+      } else if (e.key === 'Escape') {
+        setSelectedClipId(null);
+      } else if (e.key === 's' || e.key === 'S') {
+        if (selectedClipId) {
+          e.preventDefault();
+          handleSplit();
+        }
+      } else if (e.key === 'd' || e.key === 'D') {
+        if (selectedClipId && (e.metaKey || e.ctrlKey)) {
+          e.preventDefault();
+          handleDuplicate();
+        }
+      } else if (e.key === 'Delete' || e.key === 'Backspace') {
+        if (selectedClipId) {
+          e.preventDefault();
+          handleDelete();
+        }
+      }
+    };
+
+    window.addEventListener('keydown', handleKeyDown);
+    return () => window.removeEventListener('keydown', handleKeyDown);
+  }, [
+    selectedClipId,
+    handleSplit,
+    handleDuplicate,
+    handleDelete,
+    setSelectedClipId,
+    handlePlayPause,
+  ]);
+
+  // Add global mouse listeners for trimming
+  useEffect(() => {
+    if (trimmingItem) {
+      window.addEventListener('mousemove', handleTrimMove);
+      window.addEventListener('mouseup', handleTrimEnd);
+      return () => {
+        window.removeEventListener('mousemove', handleTrimMove);
+        window.removeEventListener('mouseup', handleTrimEnd);
+      };
+    }
+  }, [trimmingItem, handleTrimMove, handleTrimEnd]);
+
+  const handleDragStart = (e: React.MouseEvent, item: StoryItemDetail) => {
+    e.stopPropagation();
+    if (!tracksRef.current) return;
+
+    const rect = e.currentTarget.getBoundingClientRect();
+    setDragOffset({
+      x: e.clientX - rect.left,
+      y: e.clientY - rect.top,
+    });
+    setDragPosition({
+      x: rect.left - tracksRef.current.getBoundingClientRect().left + tracksRef.current.scrollLeft,
+      // Subtract ruler height since clips are positioned relative to tracks area, not the scrollable container
+      y: rect.top - tracksRef.current.getBoundingClientRect().top - TIME_RULER_HEIGHT,
+    });
+    setDraggingItem(item.id);
+  };
+
+  const handleDragMove = useCallback(
+    (e: React.MouseEvent) => {
+      if (!draggingItem || !tracksRef.current) return;
+
+      const rect = tracksRef.current.getBoundingClientRect();
+      const x = e.clientX - rect.left + tracksRef.current.scrollLeft - dragOffset.x;
+      // Subtract ruler height since clips are positioned relative to tracks area
+      const y = e.clientY - rect.top - dragOffset.y - TIME_RULER_HEIGHT;
+
+      setDragPosition({ x: Math.max(0, x), y });
+    },
+    [draggingItem, dragOffset],
+  );
+
+  const handleDragEnd = useCallback(() => {
+    if (!draggingItem || !tracksRef.current) {
+      setDraggingItem(null);
+      return;
+    }
+
+    const item = items.find((i) => i.id === draggingItem);
+    if (!item) {
+      setDraggingItem(null);
+      return;
+    }
+
+    // Calculate new time from x position
+    const newTimeMs = Math.max(0, Math.round(pixelsToMs(dragPosition.x)));
+
+    // Calculate new track from y position
+    const trackIndex = Math.floor(dragPosition.y / TRACK_HEIGHT);
+    const clampedTrackIndex = Math.max(0, Math.min(trackIndex, tracks.length - 1));
+    const newTrack = tracks[clampedTrackIndex] ?? 0;
+
+    // Check if position changed
+    if (newTimeMs !== item.start_time_ms || newTrack !== item.track) {
+      moveItem.mutate(
+        {
+          storyId,
+          itemId: item.id,
+          data: {
+            start_time_ms: newTimeMs,
+            track: newTrack,
+          },
+        },
+        {
+          onError: (error) => {
+            toast({
+              title: 'Failed to move item',
+              description: error instanceof Error ? error.message : String(error),
+              variant: 'destructive',
+            });
+          },
+        },
+      );
+    }
+
+    setDraggingItem(null);
+  }, [draggingItem, dragPosition, items, tracks, pixelsToMs, storyId, moveItem, toast]);
+
+  // Get track index for rendering
+  const getTrackIndex = (trackNumber: number) => tracks.indexOf(trackNumber);
+
+  // Calculate clip position and dimensions
+  const getClipStyle = (item: StoryItemDetail) => {
+    const isDragging = draggingItem === item.id;
+    const trackIndex = getTrackIndex(item.track);
+    const effectiveDuration = getEffectiveDuration(item);
+    const width = msToPixels(effectiveDuration);
+    const left = isDragging ? dragPosition.x : msToPixels(item.start_time_ms);
+    const top = isDragging ? dragPosition.y : trackIndex * TRACK_HEIGHT;
+
+    return {
+      width: `${width}px`,
+      left: `${left}px`,
+      top: `${top}px`,
+      height: `${TRACK_HEIGHT - 4}px`,
+    };
+  };
+
+  // Playhead position
+  const playheadLeft = msToPixels(currentTimeMs);
+
+  // Auto-scroll timeline to follow playhead during playback
+  useEffect(() => {
+    if (!isCurrentlyPlaying || !tracksRef.current) return;
+
+    const container = tracksRef.current;
+    const containerWidth = container.clientWidth;
+    const scrollLeft = container.scrollLeft;
+    const halfwayPoint = scrollLeft + containerWidth / 2;
+
+    // If playhead is past the halfway point, scroll to keep it centered
+    if (playheadLeft > halfwayPoint) {
+      const targetScroll = playheadLeft - containerWidth / 2;
+      container.scrollLeft = targetScroll;
+    }
+  }, [isCurrentlyPlaying, playheadLeft]);
+
+  // Calculate tracks area height
+  const tracksAreaHeight = tracks.length * TRACK_HEIGHT;
+  const timelineContainerHeight = editorHeight - 40; // Subtract toolbar height
+
+  if (items.length === 0) {
+    return null;
+  }
+
+  return (
+    <div className="fixed bottom-0 left-0 right-0 border-t bg-background/95 backdrop-blur supports-backdrop-filter:bg-background/60 z-50">
+      <div
+        className="border-t bg-background/30 backdrop-blur-2xl overflow-hidden relative"
+        ref={containerRef}
+      >
+        {/* Resize handle at top */}
+        <button
+          type="button"
+          className="absolute top-0 left-0 right-0 h-2 cursor-ns-resize flex items-center justify-center hover:bg-muted/50 transition-colors z-20 group"
+          onMouseDown={handleResizeStart}
+          aria-label="Resize track editor"
+        >
+          <GripHorizontal className="h-3 w-3 text-muted-foreground/50 group-hover:text-muted-foreground" />
+        </button>
+
+        {/* Toolbar */}
+        <div className="flex items-center justify-between px-3 py-2 border-b bg-muted/30 mt-2">
+          {/* Play controls - left side */}
+          <div className="flex items-center gap-2">
+            <Button
+              variant="ghost"
+              size="icon"
+              className="h-7 w-7"
+              onClick={handlePlayPause}
+              title="Play/Pause (Space)"
+            >
+              {isCurrentlyPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
+            </Button>
+            <Button
+              variant="ghost"
+              size="icon"
+              className="h-7 w-7"
+              onClick={handleStop}
+              disabled={!isCurrentlyPlaying}
+            >
+              <Square className="h-3 w-3" />
+            </Button>
+            <span className="text-xs text-muted-foreground tabular-nums ml-2">
+              {formatTime(currentTimeMs)} / {formatTime(totalDurationMs)}
+            </span>
+          </div>
+
+          {/* Clip editing controls - center */}
+          {selectedClipId && (
+            <div className="flex items-center gap-1">
+              <Button
+                variant="ghost"
+                size="icon"
+                className="h-7 w-7"
+                onClick={handleSplit}
+                title="Split at playhead (S)"
+              >
+                <Scissors className="h-4 w-4" />
+              </Button>
+              <Button
+                variant="ghost"
+                size="icon"
+                className="h-7 w-7"
+                onClick={handleDuplicate}
+                title="Duplicate (Cmd/Ctrl+D)"
+              >
+                <Copy className="h-4 w-4" />
+              </Button>
+              <Button
+                variant="ghost"
+                size="icon"
+                className="h-7 w-7"
+                onClick={handleDelete}
+                title="Delete (Delete/Backspace)"
+              >
+                <Trash2 className="h-4 w-4" />
+              </Button>
+            </div>
+          )}
+
+          {/* 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}>
+              <Minus className="h-3 w-3" />
+            </Button>
+            <Button variant="ghost" size="icon" className="h-6 w-6" onClick={handleZoomIn}>
+              <Plus className="h-3 w-3" />
+            </Button>
+          </div>
+        </div>
+
+        {/* Timeline container with track labels sidebar */}
+        <div className="flex" style={{ height: `${timelineContainerHeight}px` }}>
+          {/* Track labels sidebar - fixed width */}
+          <div className="w-16 shrink-0 border-r bg-muted/20 overflow-hidden">
+            {/* Spacer for time ruler */}
+            <div className="h-6 border-b bg-muted/30" />
+            {/* Track labels */}
+            <div style={{ height: `${tracksAreaHeight}px` }}>
+              {tracks.map((trackNumber, index) => (
+                <div
+                  key={trackNumber}
+                  className={cn(
+                    'border-b flex items-center justify-center',
+                    index % 2 === 0 ? 'bg-background' : 'bg-muted/10',
+                  )}
+                  style={{ height: `${TRACK_HEIGHT}px` }}
+                >
+                  <span className="text-[10px] text-muted-foreground select-none">
+                    {trackNumber}
+                  </span>
+                </div>
+              ))}
+            </div>
+          </div>
+
+          {/* Scrollable timeline area */}
+          {/* biome-ignore lint/a11y/noStaticElementInteractions: Container handles drag events for child clips */}
+          <div
+            ref={tracksRef}
+            className="overflow-auto relative flex-1"
+            onMouseMove={draggingItem ? handleDragMove : undefined}
+            onMouseUp={draggingItem ? handleDragEnd : undefined}
+            onMouseLeave={draggingItem ? handleDragEnd : undefined}
+          >
+            {/* Time ruler - clickable to seek */}
+            <button
+              type="button"
+              className="h-6 border-b bg-muted/20 sticky top-0 z-10 cursor-pointer text-left"
+              style={{ width: `${timelineWidth}px` }}
+              onClick={handleTimelineClick}
+              aria-label="Seek timeline"
+            >
+              {timeMarkers.map((ms) => (
+                <div
+                  key={ms}
+                  className="absolute top-0 h-full flex flex-col justify-end pointer-events-none"
+                  style={{ left: `${msToPixels(ms)}px` }}
+                >
+                  <div className="h-2 w-px bg-border" />
+                  <span className="text-[10px] text-muted-foreground ml-1 select-none">
+                    {formatTime(ms)}
+                  </span>
+                </div>
+              ))}
+            </button>
+
+            {/* Tracks area */}
+            <div
+              className="relative"
+              style={{ width: `${timelineWidth}px`, height: `${tracksAreaHeight}px` }}
+            >
+              {/* Track backgrounds - pointer-events-none to allow clicks to pass through */}
+              {tracks.map((trackNumber, index) => (
+                <div
+                  key={trackNumber}
+                  className={cn(
+                    'absolute left-0 right-0 border-b pointer-events-none',
+                    index % 2 === 0 ? 'bg-background' : 'bg-muted/10',
+                  )}
+                  style={{
+                    top: `${index * TRACK_HEIGHT}px`,
+                    height: `${TRACK_HEIGHT}px`,
+                  }}
+                />
+              ))}
+
+              {/* Click area for seeking - z-index lower than clips */}
+              <button
+                type="button"
+                className="absolute inset-0 z-0 cursor-pointer"
+                onClick={handleTimelineClick}
+                aria-label="Seek timeline"
+              />
+
+              {/* Audio clips */}
+              {items.map((item) => {
+                const isDragging = draggingItem === item.id;
+                const isSelected = selectedClipId === item.id;
+                const isTrimming = trimmingItem === item.id;
+
+                // Use temporary trim values during trimming for visual feedback
+                const displayTrimStart =
+                  isTrimming && tempTrimValues
+                    ? tempTrimValues.trim_start_ms
+                    : item.trim_start_ms || 0;
+                const displayTrimEnd =
+                  isTrimming && tempTrimValues ? tempTrimValues.trim_end_ms : item.trim_end_ms || 0;
+                const effectiveDuration = item.duration * 1000 - displayTrimStart - displayTrimEnd;
+
+                const style = getClipStyle({
+                  ...item,
+                  trim_start_ms: displayTrimStart,
+                  trim_end_ms: displayTrimEnd,
+                });
+                const clipWidth = msToPixels(effectiveDuration);
+
+                return (
+                  <div
+                    key={item.id}
+                    className={cn(
+                      'absolute rounded select-none overflow-visible z-10',
+                      isSelected && 'ring-2 ring-primary ring-offset-1',
+                      isTrimming && 'ring-2 ring-accent',
+                    )}
+                    style={style}
+                  >
+                    <button
+                      type="button"
+                      className={cn(
+                        'w-full h-full rounded cursor-move overflow-hidden',
+                        'bg-accent/80 hover:bg-accent border border-accent-foreground/20',
+                        'flex flex-col justify-center',
+                        isDragging && 'opacity-80 shadow-lg z-20',
+                        !isDragging && 'transition-all duration-100',
+                      )}
+                      onClick={(e) => handleClipClick(e, item)}
+                      onMouseDown={(e) => {
+                        // Only start drag if not clicking on trim handles
+                        if (!(e.target as HTMLElement).closest('.trim-handle')) {
+                          handleDragStart(e, item);
+                        }
+                      }}
+                    >
+                      {/* Clip label */}
+                      <div className="absolute top-0 left-1 right-1 z-10">
+                        <p className="text-[9px] font-medium text-accent-foreground truncate">
+                          {item.profile_name}
+                        </p>
+                      </div>
+                      {/* Waveform */}
+                      <div className="absolute inset-0 top-3">
+                        <ClipWaveform
+                          generationId={item.generation_id}
+                          width={clipWidth}
+                          trimStartMs={displayTrimStart}
+                          trimEndMs={displayTrimEnd}
+                          duration={item.duration}
+                        />
+                      </div>
+                    </button>
+
+                    {/* Trim handles */}
+                    {isSelected && (
+                      <>
+                        {/* Left trim handle */}
+                        <button
+                          type="button"
+                          className="trim-handle absolute left-0 top-0 bottom-0 w-2 cursor-ew-resize hover:bg-primary/30 bg-primary/20 z-30 rounded-l"
+                          onMouseDown={(e) => handleTrimStart(e, item, 'start')}
+                          aria-label="Trim start"
+                        />
+                        {/* Right trim handle */}
+                        <button
+                          type="button"
+                          className="trim-handle absolute right-0 top-0 bottom-0 w-2 cursor-ew-resize hover:bg-primary/30 bg-primary/20 z-30 rounded-r"
+                          onMouseDown={(e) => handleTrimStart(e, item, 'end')}
+                          aria-label="Trim end"
+                        />
+                      </>
+                    )}
+                  </div>
+                );
+              })}
+
+              {/* Playhead - always visible */}
+              <div
+                className="absolute top-0 bottom-0 w-1 bg-accent z-30 pointer-events-none rounded-full"
+                style={{ left: `${playheadLeft}px` }}
+              >
+                <div className="absolute -top-1 left-1/2 -translate-x-1/2 w-3 h-3 bg-accent rounded-full" />
+              </div>
+            </div>
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+}

app/src/components/VoiceProfiles/AudioSampleRecording.tsx

@@ -1,8 +1,31 @@
 import { Mic, Pause, Play, Square } from 'lucide-react';
+import { memo, useEffect, useState } from 'react';
+import { Visualizer } from 'react-sound-visualizer';
 import { Button } from '@/components/ui/button';
-import { FormControl, FormItem, FormLabel, FormMessage } from '@/components/ui/form';
+import { FormControl, FormItem, FormMessage } from '@/components/ui/form';
 import { formatAudioDuration } from '@/lib/utils/audio';
 
+const MemoizedWaveform = memo(function MemoizedWaveform({
+  audioStream,
+}: {
+  audioStream: MediaStream;
+}) {
+  return (
+    <div className="absolute inset-0 pointer-events-none flex items-center justify-center opacity-30">
+      <Visualizer audio={audioStream} autoStart strokeColor="#b39a3d">
+        {({ canvasRef }) => (
+          <canvas
+            ref={canvasRef}
+            width={500}
+            height={150}
+            className="w-full h-full"
+          />
+        )}
+      </Visualizer>
+    </div>
+  );
+});
+
 interface AudioSampleRecordingProps {
   file: File | null | undefined;
   isRecording: boolean;
@@ -14,6 +37,7 @@ interface AudioSampleRecordingProps {
   onPlayPause: () => void;
   isPlaying: boolean;
   isTranscribing?: boolean;
+  showWaveform?: boolean;
 }
 
 export function AudioSampleRecording({
@@ -27,29 +51,67 @@ export function AudioSampleRecording({
   onPlayPause,
   isPlaying,
   isTranscribing = false,
+  showWaveform = true,
 }: AudioSampleRecordingProps) {
+  const [audioStream, setAudioStream] = useState<MediaStream | null>(null);
+
+  // Request microphone access when component mounts
+  useEffect(() => {
+    if (!showWaveform) return;
+
+    let stream: MediaStream | null = null;
+
+    navigator.mediaDevices
+      .getUserMedia({ audio: true, video: false })
+      .then((s) => {
+        stream = s;
+        setAudioStream(s);
+      })
+      .catch((err) => {
+        console.warn('Could not access microphone for visualization:', err);
+      });
+
+    return () => {
+      if (stream) {
+        stream.getTracks().forEach((track) => {
+          track.stop();
+        });
+      }
+    };
+  }, [showWaveform]);
+
   return (
     <FormItem>
-      <FormLabel>Record Audio</FormLabel>
       <FormControl>
         <div className="space-y-4">
           {!isRecording && !file && (
-            <div className="flex flex-col items-center justify-center gap-4 p-4 border-2 border-dashed rounded-lg min-h-[180px]">
-              <Button type="button" onClick={onStart} size="lg" className="flex items-center gap-2">
+            <div className="relative flex flex-col items-center justify-center gap-4 p-4 border-2 border-dashed rounded-lg min-h-[180px] overflow-hidden">
+              {showWaveform && audioStream && (
+                <MemoizedWaveform audioStream={audioStream} />
+              )}
+              <Button
+                type="button"
+                onClick={onStart}
+                size="lg"
+                className="relative z-10 flex items-center gap-2"
+              >
                 <Mic className="h-5 w-5" />
                 Start Recording
               </Button>
-              <p className="text-sm text-muted-foreground text-center">
+              <p className="relative z-10 text-sm text-muted-foreground text-center">
                 Click to start recording. Maximum duration: 30 seconds.
               </p>
             </div>
           )}
 
           {isRecording && (
-            <div className="flex flex-col items-center justify-center gap-4 p-4 border-2 border-destructive rounded-lg bg-destructive/5 min-h-[180px]">
-              <div className="flex items-center gap-4">
+            <div className="relative flex flex-col items-center justify-center gap-4 p-4 border-2 border-accent rounded-lg bg-accent/5 min-h-[180px] overflow-hidden">
+              {showWaveform && audioStream && (
+                <MemoizedWaveform audioStream={audioStream} />
+              )}
+              <div className="relative z-10 flex items-center gap-4">
                 <div className="flex items-center gap-2">
-                  <div className="h-3 w-3 rounded-full bg-destructive animate-pulse" />
+                  <div className="h-3 w-3 rounded-full bg-accent animate-pulse" />
                   <span className="text-lg font-mono font-semibold">
                     {formatAudioDuration(duration)}
                   </span>
@@ -58,13 +120,12 @@ export function AudioSampleRecording({
               <Button
                 type="button"
                 onClick={onStop}
-                variant="destructive"
-                className="flex items-center gap-2"
+                className="relative z-10 flex items-center gap-2 bg-accent text-accent-foreground hover:bg-accent/90"
               >
                 <Square className="h-4 w-4" />
                 Stop Recording
               </Button>
-              <p className="text-sm text-muted-foreground text-center">
+              <p className="relative z-10 text-sm text-muted-foreground text-center">
                 {formatAudioDuration(30 - duration)} remaining
               </p>
             </div>

app/src/components/VoiceProfiles/AudioSampleSystem.tsx

@@ -1,6 +1,6 @@
 import { Mic, Monitor, Pause, Play, Square } from 'lucide-react';
 import { Button } from '@/components/ui/button';
-import { FormControl, FormItem, FormLabel, FormMessage } from '@/components/ui/form';
+import { FormControl, FormItem, FormMessage } from '@/components/ui/form';
 import { formatAudioDuration } from '@/lib/utils/audio';
 
 interface AudioSampleSystemProps {
@@ -30,7 +30,6 @@ export function AudioSampleSystem({
 }: AudioSampleSystemProps) {
   return (
     <FormItem>
-      <FormLabel>Capture System Audio</FormLabel>
       <FormControl>
         <div className="space-y-4">
           {!isRecording && !file && (

app/src/components/VoiceProfiles/AudioSampleUpload.tsx

@@ -1,7 +1,7 @@
 import { Mic, Pause, Play, Upload } from 'lucide-react';
 import { useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
-import { FormControl, FormItem, FormLabel, FormMessage } from '@/components/ui/form';
+import { FormControl, FormItem, FormMessage } from '@/components/ui/form';
 
 interface AudioSampleUploadProps {
   file: File | null | undefined;
@@ -31,7 +31,6 @@ export function AudioSampleUpload({
 
   return (
     <FormItem>
-      <FormLabel>Audio File</FormLabel>
       <FormControl>
         <div className="flex flex-col gap-2">
           <input

app/src/components/VoiceProfiles/ProfileCard.tsx

@@ -15,6 +15,7 @@ import {
 import type { VoiceProfileResponse } from '@/lib/api/types';
 import { useDeleteProfile, useExportProfile } from '@/lib/hooks/useProfiles';
 import { cn } from '@/lib/utils/cn';
+import { useServerStore } from '@/stores/serverStore';
 import { useUIStore } from '@/stores/uiStore';
 
 interface ProfileCardProps {
@@ -23,15 +24,19 @@ interface ProfileCardProps {
 
 export function ProfileCard({ profile }: ProfileCardProps) {
   const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [avatarError, setAvatarError] = useState(false);
   const deleteProfile = useDeleteProfile();
   const exportProfile = useExportProfile();
   const setEditingProfileId = useUIStore((state) => state.setEditingProfileId);
   const setProfileDialogOpen = useUIStore((state) => state.setProfileDialogOpen);
   const selectedProfileId = useUIStore((state) => state.selectedProfileId);
   const setSelectedProfileId = useUIStore((state) => state.setSelectedProfileId);
+  const serverUrl = useServerStore((state) => state.serverUrl);
 
   const isSelected = selectedProfileId === profile.id;
 
+  const avatarUrl = profile.avatar_path ? `${serverUrl}/profiles/${profile.id}/avatar` : null;
+
   const handleSelect = () => {
     setSelectedProfileId(isSelected ? null : profile.id);
   };
@@ -67,8 +72,20 @@ export function ProfileCard({ profile }: ProfileCardProps) {
       >
         <CardHeader className="p-3 pb-2">
           <CardTitle className="flex items-center gap-1.5 text-base font-medium">
-            <div className="h-6 w-6 rounded-full bg-muted flex items-center justify-center shrink-0">
-              <Mic className="h-3.5 w-3.5 text-muted-foreground" />
+            <div className="h-6 w-6 rounded-full bg-muted flex items-center justify-center shrink-0 overflow-hidden">
+              {avatarUrl && !avatarError ? (
+                <img
+                  src={avatarUrl}
+                  alt={`${profile.name} avatar`}
+                  className={cn(
+                    'h-full w-full object-cover transition-all duration-200',
+                    !isSelected && 'grayscale',
+                  )}
+                  onError={() => setAvatarError(true)}
+                />
+              ) : (
+                <Mic className="h-3.5 w-3.5 text-muted-foreground" />
+              )}
             </div>
             <span className="break-words">{profile.name}</span>
           </CardTitle>

app/src/components/VoiceProfiles/ProfileForm.tsx

@@ -1,6 +1,6 @@
 import { zodResolver } from '@hookform/resolvers/zod';
-import { Mic, Monitor, Upload } from 'lucide-react';
-import { useEffect, useState } from 'react';
+import { Edit2, Mic, Monitor, Upload, X } from 'lucide-react';
+import { useEffect, useRef, useState } from 'react';
 import { useForm } from 'react-hook-form';
 import * as z from 'zod';
 import { Button } from '@/components/ui/button';
@@ -36,51 +36,22 @@ import { useAudioRecording } from '@/lib/hooks/useAudioRecording';
 import {
   useAddSample,
   useCreateProfile,
+  useDeleteAvatar,
   useProfile,
   useUpdateProfile,
+  useUploadAvatar,
 } from '@/lib/hooks/useProfiles';
 import { useSystemAudioCapture } from '@/lib/hooks/useSystemAudioCapture';
 import { useTranscription } from '@/lib/hooks/useTranscription';
-import { isTauri } from '@/lib/tauri';
-import { formatAudioDuration } from '@/lib/utils/audio';
-import { useUIStore } from '@/stores/uiStore';
+import { formatAudioDuration, getAudioDuration } from '@/lib/utils/audio';
+import { usePlatform } from '@/platform/PlatformContext';
+import { useServerStore } from '@/stores/serverStore';
+import { type ProfileFormDraft, useUIStore } from '@/stores/uiStore';
 import { AudioSampleRecording } from './AudioSampleRecording';
 import { AudioSampleSystem } from './AudioSampleSystem';
 import { AudioSampleUpload } from './AudioSampleUpload';
 import { SampleList } from './SampleList';
 
-// Helper function to get audio duration from File
-async function getAudioDuration(file: File & { recordedDuration?: number }): Promise<number> {
-  // If the file has a recordedDuration property (from our 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.
-  if (file.recordedDuration !== undefined && Number.isFinite(file.recordedDuration)) {
-    return file.recordedDuration;
-  }
-
-  return new Promise((resolve, reject) => {
-    const audio = new Audio();
-    const url = URL.createObjectURL(file);
-
-    audio.addEventListener('loadedmetadata', () => {
-      URL.revokeObjectURL(url);
-      // Check if duration is valid (not Infinity or NaN)
-      if (Number.isFinite(audio.duration) && audio.duration > 0) {
-        resolve(audio.duration);
-      } else {
-        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;
-  });
-}
-
 const MAX_AUDIO_DURATION_SECONDS = 30;
 
 const baseProfileSchema = z.object({
@@ -89,6 +60,7 @@ const baseProfileSchema = z.object({
   language: z.enum(LANGUAGE_CODES as [LanguageCode, ...LanguageCode[]]),
   sampleFile: z.instanceof(File).optional(),
   referenceText: z.string().max(1000).optional(),
+  avatarFile: z.instanceof(File).optional(),
 });
 
 const profileSchema = baseProfileSchema.refine(
@@ -107,22 +79,52 @@ const profileSchema = baseProfileSchema.refine(
 
 type ProfileFormValues = z.infer<typeof profileSchema>;
 
+// Helper to convert File to base64
+async function fileToBase64(file: File): Promise<string> {
+  return new Promise((resolve, reject) => {
+    const reader = new FileReader();
+    reader.onload = () => resolve(reader.result as string);
+    reader.onerror = reject;
+    reader.readAsDataURL(file);
+  });
+}
+
+// Helper to convert base64 to File
+function base64ToFile(base64: string, fileName: string, fileType: string): File {
+  const arr = base64.split(',');
+  const bstr = atob(arr[1]);
+  let n = bstr.length;
+  const u8arr = new Uint8Array(n);
+  while (n--) {
+    u8arr[n] = bstr.charCodeAt(n);
+  }
+  return new File([u8arr], fileName, { type: fileType });
+}
+
 export function ProfileForm() {
+  const platform = usePlatform();
   const open = useUIStore((state) => state.profileDialogOpen);
   const setOpen = useUIStore((state) => state.setProfileDialogOpen);
   const editingProfileId = useUIStore((state) => state.editingProfileId);
   const setEditingProfileId = useUIStore((state) => state.setEditingProfileId);
+  const profileFormDraft = useUIStore((state) => state.profileFormDraft);
+  const setProfileFormDraft = useUIStore((state) => state.setProfileFormDraft);
   const { data: editingProfile } = useProfile(editingProfileId || '');
   const createProfile = useCreateProfile();
   const updateProfile = useUpdateProfile();
   const addSample = useAddSample();
+  const uploadAvatar = useUploadAvatar();
+  const deleteAvatar = useDeleteAvatar();
   const transcribe = useTranscription();
   const { toast } = useToast();
-  const [sampleMode, setSampleMode] = useState<'upload' | 'record' | 'system'>('upload');
+  const [sampleMode, setSampleMode] = useState<'upload' | 'record' | 'system'>('record');
   const [audioDuration, setAudioDuration] = useState<number | null>(null);
   const [isValidatingAudio, setIsValidatingAudio] = useState(false);
+  const [avatarPreview, setAvatarPreview] = useState<string | null>(null);
+  const avatarInputRef = useRef<HTMLInputElement>(null);
   const { isPlaying, playPause, cleanup: cleanupAudio } = useAudioPlayer();
   const isCreating = !editingProfileId;
+  const serverUrl = useServerStore((state) => state.serverUrl);
 
   const form = useForm<ProfileFormValues>({
     resolver: zodResolver(profileSchema),
@@ -132,10 +134,12 @@ export function ProfileForm() {
       language: 'en',
       sampleFile: undefined,
       referenceText: '',
+      avatarFile: undefined,
     },
   });
 
   const selectedFile = form.watch('sampleFile');
+  const selectedAvatarFile = form.watch('avatarFile');
 
   // Validate audio duration when file is selected
   useEffect(() => {
@@ -187,7 +191,7 @@ export function ProfileForm() {
     stopRecording,
     cancelRecording,
   } = useAudioRecording({
-    maxDurationSeconds: 30,
+    maxDurationSeconds: 29,
     onRecordingComplete: (blob, recordedDuration) => {
       const file = new File([blob], `recording-${Date.now()}.webm`, {
         type: blob.type || 'audio/webm',
@@ -213,7 +217,7 @@ export function ProfileForm() {
     stopRecording: stopSystemRecording,
     cancelRecording: cancelSystemRecording,
   } = useSystemAudioCapture({
-    maxDurationSeconds: 30,
+    maxDurationSeconds: 29,
     onRecordingComplete: (blob, recordedDuration) => {
       const file = new File([blob], `system-audio-${Date.now()}.wav`, {
         type: blob.type || 'audio/wav',
@@ -252,6 +256,20 @@ export function ProfileForm() {
     }
   }, [systemRecordingError, toast]);
 
+  // Handle avatar preview
+  useEffect(() => {
+    if (selectedAvatarFile instanceof File) {
+      const url = URL.createObjectURL(selectedAvatarFile);
+      setAvatarPreview(url);
+      return () => URL.revokeObjectURL(url);
+    } else if (editingProfile?.avatar_path) {
+      setAvatarPreview(`${serverUrl}/profiles/${editingProfile.id}/avatar`);
+    } else {
+      setAvatarPreview(null);
+    }
+  }, [selectedAvatarFile, editingProfile, serverUrl]);
+
+  // Restore form state from draft or editing profile
   useEffect(() => {
     if (editingProfile) {
       form.reset({
@@ -260,18 +278,46 @@ export function ProfileForm() {
         language: editingProfile.language as LanguageCode,
         sampleFile: undefined,
         referenceText: undefined,
+        avatarFile: undefined,
       });
-    } else {
+    } else if (profileFormDraft && open) {
+      // Restore from draft when opening in create mode
+      form.reset({
+        name: profileFormDraft.name,
+        description: profileFormDraft.description,
+        language: profileFormDraft.language as LanguageCode,
+        referenceText: profileFormDraft.referenceText,
+        sampleFile: undefined,
+        avatarFile: undefined,
+      });
+      setSampleMode(profileFormDraft.sampleMode);
+      // Restore the file if we have it saved
+      if (
+        profileFormDraft.sampleFileData &&
+        profileFormDraft.sampleFileName &&
+        profileFormDraft.sampleFileType
+      ) {
+        const file = base64ToFile(
+          profileFormDraft.sampleFileData,
+          profileFormDraft.sampleFileName,
+          profileFormDraft.sampleFileType,
+        );
+        form.setValue('sampleFile', file);
+      }
+    } else if (!open) {
+      // Only reset to defaults when modal is closed and no draft
       form.reset({
         name: '',
         description: '',
         language: 'en',
         sampleFile: undefined,
         referenceText: undefined,
+        avatarFile: undefined,
       });
-      setSampleMode('upload');
+      setSampleMode('record');
+      setAvatarPreview(null);
     }
-  }, [editingProfile, form]);
+  }, [editingProfile, profileFormDraft, open, form]);
 
   async function handleTranscribe() {
     const file = form.getValues('sampleFile');
@@ -313,6 +359,52 @@ export function ProfileForm() {
     playPause(file);
   }
 
+  function handleAvatarFileChange(e: React.ChangeEvent<HTMLInputElement>) {
+    const file = e.target.files?.[0];
+    if (file) {
+      if (!file.type.startsWith('image/')) {
+        toast({
+          title: 'Invalid file type',
+          description: 'Please select an image file (PNG, JPG, or WebP)',
+          variant: 'destructive',
+        });
+        return;
+      }
+      if (file.size > 5 * 1024 * 1024) {
+        toast({
+          title: 'File too large',
+          description: 'Image must be less than 5MB',
+          variant: 'destructive',
+        });
+        return;
+      }
+      form.setValue('avatarFile', file);
+    }
+  }
+
+  async function handleRemoveAvatar() {
+    if (editingProfileId && editingProfile?.avatar_path) {
+      try {
+        await deleteAvatar.mutateAsync(editingProfileId);
+        toast({
+          title: 'Avatar removed',
+          description: 'Avatar image has been removed successfully.',
+        });
+      } catch (error) {
+        toast({
+          title: 'Failed to remove avatar',
+          description: error instanceof Error ? error.message : 'Unknown error',
+          variant: 'destructive',
+        });
+      }
+    }
+    form.setValue('avatarFile', undefined);
+    setAvatarPreview(null);
+    if (avatarInputRef.current) {
+      avatarInputRef.current.value = '';
+    }
+  }
+
   async function onSubmit(data: ProfileFormValues) {
     try {
       if (editingProfileId) {
@@ -325,6 +417,24 @@ export function ProfileForm() {
             language: data.language,
           },
         });
+
+        // Handle avatar upload/update if file changed
+        if (data.avatarFile) {
+          try {
+            await uploadAvatar.mutateAsync({
+              profileId: editingProfileId,
+              file: data.avatarFile,
+            });
+          } catch (avatarError) {
+            toast({
+              title: 'Avatar upload failed',
+              description:
+                avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
+              variant: 'destructive',
+            });
+          }
+        }
+
         toast({
           title: 'Voice updated',
           description: `"${data.name}" has been updated successfully.`,
@@ -401,6 +511,24 @@ export function ProfileForm() {
             file: sampleFile,
             referenceText: referenceText,
           });
+
+          // Handle avatar upload if provided
+          if (data.avatarFile) {
+            try {
+              await uploadAvatar.mutateAsync({
+                profileId: profile.id,
+                file: data.avatarFile,
+              });
+            } catch (avatarError) {
+              toast({
+                title: 'Avatar upload failed',
+                description:
+                  avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
+                variant: 'destructive',
+              });
+            }
+          }
+
           toast({
             title: 'Profile created',
             description: `"${data.name}" has been created with a sample.`,
@@ -415,6 +543,8 @@ export function ProfileForm() {
         }
       }
 
+      // Clear draft and reset form on success
+      setProfileFormDraft(null);
       form.reset();
       setEditingProfileId(null);
       setOpen(false);
@@ -427,12 +557,41 @@ export function ProfileForm() {
     }
   }
 
-  function handleOpenChange(open: boolean) {
-    setOpen(open);
-    if (!open) {
+  async function handleOpenChange(newOpen: boolean) {
+    if (!newOpen && isCreating) {
+      // Save draft when closing the create modal
+      const values = form.getValues();
+      const hasContent =
+        values.name || values.description || values.referenceText || values.sampleFile;
+
+      if (hasContent) {
+        const draft: ProfileFormDraft = {
+          name: values.name || '',
+          description: values.description || '',
+          language: values.language || 'en',
+          referenceText: values.referenceText || '',
+          sampleMode,
+        };
+
+        // Save file as base64 if present
+        if (values.sampleFile) {
+          try {
+            draft.sampleFileName = values.sampleFile.name;
+            draft.sampleFileType = values.sampleFile.type;
+            draft.sampleFileData = await fileToBase64(values.sampleFile);
+          } catch {
+            // If file conversion fails, just don't save the file
+          }
+        }
+
+        setProfileFormDraft(draft);
+      }
+    }
+
+    setOpen(newOpen);
+    if (!newOpen) {
       setEditingProfileId(null);
-      form.reset();
-      setSampleMode('upload');
+      // Don't reset form here - let the effect handle it based on draft state
       if (isRecording) {
         cancelRecording();
       }
@@ -445,174 +604,119 @@ export function ProfileForm() {
 
   return (
     <Dialog open={open} onOpenChange={handleOpenChange}>
-      <DialogContent className="max-w-4xl">
-        <DialogHeader>
-          <DialogTitle>{editingProfileId ? 'Edit Voice' : 'Create Voice Profile'}</DialogTitle>
-          <DialogDescription>
-            {editingProfileId
-              ? 'Update your voice profile details and manage samples.'
-              : 'Create a new voice profile with an audio sample to clone the voice.'}
-          </DialogDescription>
-        </DialogHeader>
-
-        <Form {...form}>
-          <form onSubmit={form.handleSubmit(onSubmit)}>
-            <div className="grid gap-6 grid-cols-2">
-              {/* Left column: Profile info */}
-              <div className="space-y-4">
-                <FormField
-                  control={form.control}
-                  name="name"
-                  render={({ field }) => (
-                    <FormItem>
-                      <FormLabel>Name</FormLabel>
-                      <FormControl>
-                        <Input placeholder="My Voice" {...field} />
-                      </FormControl>
-                      <FormMessage />
-                    </FormItem>
-                  )}
-                />
-
-                <FormField
-                  control={form.control}
-                  name="description"
-                  render={({ field }) => (
-                    <FormItem>
-                      <FormLabel>Description (Optional)</FormLabel>
-                      <FormControl>
-                        <Textarea placeholder="Describe this voice..." {...field} />
-                      </FormControl>
-                      <FormMessage />
-                    </FormItem>
-                  )}
-                />
-
-                <FormField
-                  control={form.control}
-                  name="language"
-                  render={({ field }) => (
-                    <FormItem>
-                      <FormLabel>Language</FormLabel>
-                      <Select onValueChange={field.onChange} defaultValue={field.value}>
-                        <FormControl>
-                          <SelectTrigger>
-                            <SelectValue />
-                          </SelectTrigger>
-                        </FormControl>
-                        <SelectContent>
-                          {LANGUAGE_OPTIONS.map((lang) => (
-                            <SelectItem key={lang.value} value={lang.value}>
-                              {lang.label}
-                            </SelectItem>
-                          ))}
-                        </SelectContent>
-                      </Select>
-                      <FormMessage />
-                    </FormItem>
-                  )}
-                />
+      <DialogContent className="max-w-none w-screen h-screen left-0 top-0 translate-x-0 translate-y-0 rounded-none p-6 overflow-y-auto">
+        <div className="max-w-5xl max-h-[85vh] mx-auto my-auto w-full flex flex-col">
+          <DialogHeader>
+            <DialogTitle className="text-2xl">
+              {editingProfileId ? 'Edit Voice' : 'Clone voice'}
+            </DialogTitle>
+            <DialogDescription>
+              {editingProfileId
+                ? 'Update your voice profile details and manage samples.'
+                : 'Create a new voice profile with an audio sample to clone the voice.'}
+            </DialogDescription>
+            {isCreating && profileFormDraft && (
+              <div className="flex items-center gap-2 pt-2">
+                <span className="text-xs text-muted-foreground">Draft restored</span>
+                <Button
+                  type="button"
+                  variant="ghost"
+                  size="sm"
+                  className="h-6 px-2 text-xs text-muted-foreground"
+                  onClick={() => {
+                    setProfileFormDraft(null);
+                    form.reset({
+                      name: '',
+                      description: '',
+                      language: 'en',
+                      sampleFile: undefined,
+                      referenceText: '',
+                    });
+                    setSampleMode('record');
+                  }}
+                >
+                  <X className="h-3 w-3 mr-1" />
+                  Discard
+                </Button>
               </div>
+            )}
+          </DialogHeader>
 
-              {/* Right column: Sample management */}
-              <div className="space-y-4 border-l pl-6">
-                {isCreating ? (
-                  <>
-                    <div>
-                      <h3 className="text-sm font-medium mb-2">Add Sample</h3>
-                      <p className="text-sm text-muted-foreground mb-4">
-                        Provide an audio sample to clone the voice. You can add more samples later.
-                      </p>
-                    </div>
-
-                    <Tabs
-                      value={sampleMode}
-                      onValueChange={(v) => {
-                        const newMode = v as 'upload' | 'record' | 'system';
-                        // Cancel any active recordings when switching modes
-                        if (isRecording && newMode !== 'record') {
-                          cancelRecording();
-                        }
-                        if (isSystemRecording && newMode !== 'system') {
-                          cancelSystemRecording();
-                        }
-                        setSampleMode(newMode);
-                      }}
-                    >
-                      <TabsList
-                        className={`grid w-full ${isTauri() && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
+          <Form {...form}>
+            <form onSubmit={form.handleSubmit(onSubmit)} className="flex-1 min-h-0 flex flex-col">
+              <div className="grid gap-6 grid-cols-2 flex-1 overflow-y-auto min-h-0">
+                {/* Left column: Sample management */}
+                <div className="space-y-4 border-r pr-6">
+                  {isCreating ? (
+                    <>
+                      <Tabs
+                        className="pt-4"
+                        value={sampleMode}
+                        onValueChange={(v) => {
+                          const newMode = v as 'upload' | 'record' | 'system';
+                          // Cancel any active recordings when switching modes
+                          if (isRecording && newMode !== 'record') {
+                            cancelRecording();
+                          }
+                          if (isSystemRecording && newMode !== 'system') {
+                            cancelSystemRecording();
+                          }
+                          setSampleMode(newMode);
+                        }}
                       >
-                        <TabsTrigger value="upload" className="flex items-center gap-2">
-                          <Upload className="h-4 w-4 shrink-0" />
-                          Upload
-                        </TabsTrigger>
-                        <TabsTrigger value="record" className="flex items-center gap-2">
-                          <Mic className="h-4 w-4 shrink-0" />
-                          Record
-                        </TabsTrigger>
-                        {isTauri() && isSystemAudioSupported && (
-                          <TabsTrigger value="system" className="flex items-center gap-2">
-                            <Monitor className="h-4 w-4 shrink-0" />
-                            System Audio
+                        <TabsList
+                          className={`grid w-full ${platform.metadata.isTauri && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
+                        >
+                          <TabsTrigger value="upload" className="flex items-center gap-2">
+                            <Upload className="h-4 w-4 shrink-0" />
+                            Upload
                           </TabsTrigger>
-                        )}
-                      </TabsList>
-
-                      <TabsContent value="upload" className="space-y-4">
-                        <FormField
-                          control={form.control}
-                          name="sampleFile"
-                          render={({ field: { onChange, name } }) => (
-                            <AudioSampleUpload
-                              file={selectedFile}
-                              onFileChange={onChange}
-                              onTranscribe={handleTranscribe}
-                              onPlayPause={handlePlayPause}
-                              isPlaying={isPlaying}
-                              isValidating={isValidatingAudio}
-                              isTranscribing={transcribe.isPending}
-                              isDisabled={
-                                audioDuration !== null && audioDuration > MAX_AUDIO_DURATION_SECONDS
-                              }
-                              fieldName={name}
-                            />
+                          <TabsTrigger value="record" className="flex items-center gap-2">
+                            <Mic className="h-4 w-4 shrink-0" />
+                            Record
+                          </TabsTrigger>
+                          {platform.metadata.isTauri && isSystemAudioSupported && (
+                            <TabsTrigger value="system" className="flex items-center gap-2">
+                              <Monitor className="h-4 w-4 shrink-0" />
+                              System Audio
+                            </TabsTrigger>
                           )}
-                        />
-                      </TabsContent>
+                        </TabsList>
 
-                      <TabsContent value="record" className="space-y-4">
-                        <FormField
-                          control={form.control}
-                          name="sampleFile"
-                          render={() => (
-                            <AudioSampleRecording
-                              file={selectedFile}
-                              isRecording={isRecording}
-                              duration={duration}
-                              onStart={startRecording}
-                              onStop={stopRecording}
-                              onCancel={handleCancelRecording}
-                              onTranscribe={handleTranscribe}
-                              onPlayPause={handlePlayPause}
-                              isPlaying={isPlaying}
-                              isTranscribing={transcribe.isPending}
-                            />
-                          )}
-                        />
-                      </TabsContent>
+                        <TabsContent value="upload" className="space-y-4">
+                          <FormField
+                            control={form.control}
+                            name="sampleFile"
+                            render={({ field: { onChange, name } }) => (
+                              <AudioSampleUpload
+                                file={selectedFile}
+                                onFileChange={onChange}
+                                onTranscribe={handleTranscribe}
+                                onPlayPause={handlePlayPause}
+                                isPlaying={isPlaying}
+                                isValidating={isValidatingAudio}
+                                isTranscribing={transcribe.isPending}
+                                isDisabled={
+                                  audioDuration !== null &&
+                                  audioDuration > MAX_AUDIO_DURATION_SECONDS
+                                }
+                                fieldName={name}
+                              />
+                            )}
+                          />
+                        </TabsContent>
 
-                      {isTauri() && isSystemAudioSupported && (
-                        <TabsContent value="system" className="space-y-4">
+                        <TabsContent value="record" className="space-y-4">
                           <FormField
                             control={form.control}
                             name="sampleFile"
                             render={() => (
-                              <AudioSampleSystem
+                              <AudioSampleRecording
                                 file={selectedFile}
-                                isRecording={isSystemRecording}
-                                duration={systemDuration}
-                                onStart={startSystemRecording}
-                                onStop={stopSystemRecording}
+                                isRecording={isRecording}
+                                duration={duration}
+                                onStart={startRecording}
+                                onStop={stopRecording}
                                 onCancel={handleCancelRecording}
                                 onTranscribe={handleTranscribe}
                                 onPlayPause={handlePlayPause}
@@ -622,55 +726,188 @@ export function ProfileForm() {
                             )}
                           />
                         </TabsContent>
-                      )}
-                    </Tabs>
 
-                    <FormField
-                      control={form.control}
-                      name="referenceText"
-                      render={({ field }) => (
-                        <FormItem>
-                          <FormLabel>Reference Text</FormLabel>
-                          <FormControl>
-                            <Textarea
-                              placeholder="Enter the exact text spoken in the audio..."
-                              className="min-h-[100px]"
-                              {...field}
+                        {platform.metadata.isTauri && isSystemAudioSupported && (
+                          <TabsContent value="system" className="space-y-4">
+                            <FormField
+                              control={form.control}
+                              name="sampleFile"
+                              render={() => (
+                                <AudioSampleSystem
+                                  file={selectedFile}
+                                  isRecording={isSystemRecording}
+                                  duration={systemDuration}
+                                  onStart={startSystemRecording}
+                                  onStop={stopSystemRecording}
+                                  onCancel={handleCancelRecording}
+                                  onTranscribe={handleTranscribe}
+                                  onPlayPause={handlePlayPause}
+                                  isPlaying={isPlaying}
+                                  isTranscribing={transcribe.isPending}
+                                />
+                              )}
                             />
-                          </FormControl>
-                          <FormMessage />
-                        </FormItem>
-                      )}
-                    />
-                  </>
-                ) : (
-                  // Show sample list when editing
-                  editingProfileId && (
-                    <div>
-                      <SampleList profileId={editingProfileId} />
-                    </div>
-                  )
-                )}
-              </div>
-            </div>
+                          </TabsContent>
+                        )}
+                      </Tabs>
 
-            <div className="flex gap-2 justify-end mt-6 pt-4 border-t">
-              <Button type="button" variant="outline" onClick={() => handleOpenChange(false)}>
-                Cancel
-              </Button>
-              <Button
-                type="submit"
-                disabled={createProfile.isPending || updateProfile.isPending || addSample.isPending}
-              >
-                {createProfile.isPending || updateProfile.isPending || addSample.isPending
-                  ? 'Saving...'
-                  : editingProfileId
-                    ? 'Save Changes'
-                    : 'Create Profile'}
-              </Button>
-            </div>
-          </form>
-        </Form>
+                      <FormField
+                        control={form.control}
+                        name="referenceText"
+                        render={({ field }) => (
+                          <FormItem>
+                            <FormLabel>Reference Text</FormLabel>
+                            <FormControl>
+                              <Textarea
+                                placeholder="Enter the exact text spoken in the audio..."
+                                className="min-h-[100px]"
+                                {...field}
+                              />
+                            </FormControl>
+                            <FormMessage />
+                          </FormItem>
+                        )}
+                      />
+                    </>
+                  ) : (
+                    // Show sample list when editing
+                    editingProfileId && (
+                      <div>
+                        <SampleList profileId={editingProfileId} />
+                      </div>
+                    )
+                  )}
+                </div>
+
+                {/* Right column: Profile info */}
+                <div className="space-y-4">
+                  {/* Avatar Upload */}
+                  <FormField
+                    control={form.control}
+                    name="avatarFile"
+                    render={() => (
+                      <FormItem>
+                        <FormControl>
+                          <div className="flex justify-center pt-4 pb-2">
+                            <div className="relative group">
+                              <div className="h-24 w-24 rounded-full bg-muted flex items-center justify-center shrink-0 overflow-hidden border-2 border-border">
+                                {avatarPreview ? (
+                                  <img
+                                    src={avatarPreview}
+                                    alt="Avatar preview"
+                                    className="h-full w-full object-cover"
+                                  />
+                                ) : (
+                                  <Mic className="h-10 w-10 text-muted-foreground" />
+                                )}
+                              </div>
+                              <button
+                                type="button"
+                                onClick={() => avatarInputRef.current?.click()}
+                                className="absolute inset-0 rounded-full bg-accent/60 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center cursor-pointer"
+                              >
+                                <Edit2 className="h-6 w-6 text-accent-foreground" />
+                              </button>
+                              {(avatarPreview || editingProfile?.avatar_path) && (
+                                <button
+                                  type="button"
+                                  onClick={handleRemoveAvatar}
+                                  disabled={deleteAvatar.isPending}
+                                  className="absolute bottom-0 right-0 h-6 w-6 rounded-full bg-background/60 backdrop-blur-sm text-muted-foreground flex items-center justify-center hover:bg-background/80 hover:text-foreground transition-colors shadow-sm border border-border/50"
+                                >
+                                  <X className="h-3.5 w-3.5" />
+                                </button>
+                              )}
+                            </div>
+                            <input
+                              ref={avatarInputRef}
+                              type="file"
+                              accept="image/png,image/jpeg,image/webp"
+                              onChange={handleAvatarFileChange}
+                              className="hidden"
+                            />
+                          </div>
+                        </FormControl>
+                        <FormMessage />
+                      </FormItem>
+                    )}
+                  />
+
+                  <FormField
+                    control={form.control}
+                    name="name"
+                    render={({ field }) => (
+                      <FormItem>
+                        <FormLabel>Name</FormLabel>
+                        <FormControl>
+                          <Input placeholder="My Voice" {...field} />
+                        </FormControl>
+                        <FormMessage />
+                      </FormItem>
+                    )}
+                  />
+
+                  <FormField
+                    control={form.control}
+                    name="description"
+                    render={({ field }) => (
+                      <FormItem>
+                        <FormLabel>Description (Optional)</FormLabel>
+                        <FormControl>
+                          <Textarea placeholder="Describe this voice..." {...field} />
+                        </FormControl>
+                        <FormMessage />
+                      </FormItem>
+                    )}
+                  />
+
+                  <FormField
+                    control={form.control}
+                    name="language"
+                    render={({ field }) => (
+                      <FormItem>
+                        <FormLabel>Language</FormLabel>
+                        <Select onValueChange={field.onChange} defaultValue={field.value}>
+                          <FormControl>
+                            <SelectTrigger>
+                              <SelectValue />
+                            </SelectTrigger>
+                          </FormControl>
+                          <SelectContent>
+                            {LANGUAGE_OPTIONS.map((lang) => (
+                              <SelectItem key={lang.value} value={lang.value}>
+                                {lang.label}
+                              </SelectItem>
+                            ))}
+                          </SelectContent>
+                        </Select>
+                        <FormMessage />
+                      </FormItem>
+                    )}
+                  />
+                </div>
+              </div>
+
+              <div className="flex gap-2 justify-end mt-6 pt-4 border-t">
+                <Button type="button" variant="outline" onClick={() => handleOpenChange(false)}>
+                  Cancel
+                </Button>
+                <Button
+                  type="submit"
+                  disabled={
+                    createProfile.isPending || updateProfile.isPending || addSample.isPending
+                  }
+                >
+                  {createProfile.isPending || updateProfile.isPending || addSample.isPending
+                    ? 'Saving...'
+                    : editingProfileId
+                      ? 'Save Changes'
+                      : 'Create Profile'}
+                </Button>
+              </div>
+            </form>
+          </Form>
+        </div>
       </DialogContent>
     </Dialog>
   );

app/src/components/VoiceProfiles/SampleList.tsx

@@ -1,11 +1,141 @@
-import { Plus, Trash2, Play } from 'lucide-react';
-import { useState } from 'react';
+import { Check, Edit, Pause, Play, Plus, Trash2, Volume2, X } from 'lucide-react';
+import { useEffect, useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
-import { useDeleteSample, useProfileSamples } from '@/lib/hooks/useProfiles';
-import { usePlayerStore } from '@/stores/playerStore';
+import { CircleButton } from '@/components/ui/circle-button';
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from '@/components/ui/dialog';
+import { Slider } from '@/components/ui/slider';
+import { Textarea } from '@/components/ui/textarea';
+import { useToast } from '@/components/ui/use-toast';
 import { apiClient } from '@/lib/api/client';
+import { useDeleteSample, useProfileSamples, useUpdateSample } from '@/lib/hooks/useProfiles';
+import { formatAudioDuration } from '@/lib/utils/audio';
+import { cn } from '@/lib/utils/cn';
 import { SampleUpload } from './SampleUpload';
 
+interface MiniSamplePlayerProps {
+  audioUrl: string;
+}
+
+function MiniSamplePlayer({ audioUrl }: MiniSamplePlayerProps) {
+  const audioRef = useRef<HTMLAudioElement | null>(null);
+  const [isPlaying, setIsPlaying] = useState(false);
+  const [currentTime, setCurrentTime] = useState(0);
+  const [duration, setDuration] = useState(0);
+  const [isLoading, setIsLoading] = useState(true);
+
+  useEffect(() => {
+    const audio = new Audio(audioUrl);
+    audioRef.current = audio;
+
+    const handleLoadedMetadata = () => {
+      setDuration(audio.duration);
+      setIsLoading(false);
+    };
+
+    const handleTimeUpdate = () => {
+      setCurrentTime(audio.currentTime);
+    };
+
+    const handleEnded = () => {
+      setIsPlaying(false);
+      setCurrentTime(0);
+    };
+
+    const handlePlay = () => setIsPlaying(true);
+    const handlePause = () => setIsPlaying(false);
+
+    audio.addEventListener('loadedmetadata', handleLoadedMetadata);
+    audio.addEventListener('timeupdate', handleTimeUpdate);
+    audio.addEventListener('ended', handleEnded);
+    audio.addEventListener('play', handlePlay);
+    audio.addEventListener('pause', handlePause);
+
+    return () => {
+      audio.pause();
+      audio.removeEventListener('loadedmetadata', handleLoadedMetadata);
+      audio.removeEventListener('timeupdate', handleTimeUpdate);
+      audio.removeEventListener('ended', handleEnded);
+      audio.removeEventListener('play', handlePlay);
+      audio.removeEventListener('pause', handlePause);
+      audio.src = '';
+    };
+  }, [audioUrl]);
+
+  const handlePlayPause = () => {
+    if (!audioRef.current) return;
+    if (isPlaying) {
+      audioRef.current.pause();
+    } else {
+      audioRef.current.play();
+    }
+  };
+
+  const handleSeek = (value: number[]) => {
+    if (!audioRef.current || duration === 0) return;
+    const progress = value[0] / 100;
+    audioRef.current.currentTime = progress * duration;
+  };
+
+  const handleStop = () => {
+    if (audioRef.current) {
+      audioRef.current.pause();
+      audioRef.current.currentTime = 0;
+    }
+    setIsPlaying(false);
+    setCurrentTime(0);
+  };
+
+  return (
+    <div className="border-t bg-muted/30 px-3 py-2 mt-2">
+      <div className="flex items-center gap-2">
+        <Button
+          type="button"
+          variant="ghost"
+          size="icon"
+          className="h-7 w-7 shrink-0"
+          onClick={handlePlayPause}
+          disabled={isLoading}
+        >
+          {isPlaying ? <Pause className="h-3.5 w-3.5" /> : <Play className="h-3.5 w-3.5 ml-0.5" />}
+        </Button>
+
+        <div className="flex-1 min-w-0 flex items-center gap-2">
+          <Slider
+            value={duration > 0 ? [(currentTime / duration) * 100] : [0]}
+            onValueChange={handleSeek}
+            max={100}
+            step={0.1}
+            className="flex-1"
+          />
+          <div className="flex items-center gap-1 text-xs text-muted-foreground shrink-0 min-w-[70px]">
+            <span className="font-mono">{formatAudioDuration(currentTime)}</span>
+            <span>/</span>
+            <span className="font-mono">{formatAudioDuration(duration)}</span>
+          </div>
+        </div>
+
+        <Button
+          type="button"
+          variant="ghost"
+          size="icon"
+          className="h-7 w-7 shrink-0"
+          onClick={handleStop}
+          title="Stop"
+        >
+          <X className="h-3.5 w-3.5" />
+        </Button>
+      </div>
+    </div>
+  );
+}
+
 interface SampleListProps {
   profileId: string;
 }
@@ -13,20 +143,62 @@ interface SampleListProps {
 export function SampleList({ profileId }: SampleListProps) {
   const { data: samples, isLoading } = useProfileSamples(profileId);
   const deleteSample = useDeleteSample();
+  const updateSample = useUpdateSample();
+  const { toast } = useToast();
   const [uploadOpen, setUploadOpen] = useState(false);
-  const setAudio = usePlayerStore((state) => state.setAudio);
-  const currentAudioId = usePlayerStore((state) => state.audioId);
-  const isPlaying = usePlayerStore((state) => state.isPlaying);
+  const [editingSampleId, setEditingSampleId] = useState<string | null>(null);
+  const [editedText, setEditedText] = useState<string>('');
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [sampleToDelete, setSampleToDelete] = useState<string | null>(null);
 
-  const handleDelete = (sampleId: string) => {
-    if (confirm('Are you sure you want to delete this sample?')) {
-      deleteSample.mutate(sampleId);
+  const handleDeleteClick = (sampleId: string) => {
+    setSampleToDelete(sampleId);
+    setDeleteDialogOpen(true);
+  };
+
+  const handleDeleteConfirm = () => {
+    if (sampleToDelete) {
+      deleteSample.mutate(sampleToDelete);
+      setDeleteDialogOpen(false);
+      setSampleToDelete(null);
     }
   };
 
-  const handlePlay = (referenceText: string, sampleId: string) => {
-    const audioUrl = apiClient.getSampleUrl(sampleId);
-    setAudio(audioUrl, sampleId, referenceText.substring(0, 50));
+  const handleStartEdit = (sampleId: string, currentText: string) => {
+    setEditingSampleId(sampleId);
+    setEditedText(currentText);
+  };
+
+  const handleCancelEdit = () => {
+    setEditingSampleId(null);
+    setEditedText('');
+  };
+
+  const handleSaveEdit = async (sampleId: string) => {
+    if (!editedText.trim()) {
+      toast({
+        title: 'Invalid text',
+        description: 'Reference text cannot be empty.',
+        variant: 'destructive',
+      });
+      return;
+    }
+
+    try {
+      await updateSample.mutateAsync({ sampleId, referenceText: editedText.trim() });
+      toast({
+        title: 'Sample updated',
+        description: 'Reference text has been updated successfully.',
+      });
+      setEditingSampleId(null);
+      setEditedText('');
+    } catch (error) {
+      toast({
+        title: 'Update failed',
+        description: error instanceof Error ? error.message : 'Failed to update sample',
+        variant: 'destructive',
+      });
+    }
   };
 
   if (isLoading) {
@@ -34,57 +206,152 @@ export function SampleList({ profileId }: SampleListProps) {
   }
 
   return (
-    <div className="space-y-4">
-      <div className="flex items-center justify-between">
-        <h3 className="text-lg font-semibold">Audio Samples</h3>
-        <Button type="button" size="sm" onClick={() => setUploadOpen(true)}>
-          <Plus className="mr-2 h-4 w-4" />
-          Add Sample
-        </Button>
-      </div>
-
+    <div className="space-y-4 pt-4">
       {samples && samples.length === 0 ? (
-        <div className="text-sm text-muted-foreground py-4">
-          No samples yet. Add your first audio sample.
+        <div className="flex flex-col items-center justify-center py-8 text-center border border-dashed rounded-lg">
+          <Volume2 className="h-8 w-8 text-muted-foreground/50 mb-2" />
+          <p className="text-sm text-muted-foreground">No samples yet</p>
+          <p className="text-xs text-muted-foreground/70 mt-1">
+            Add your first audio sample to get started
+          </p>
         </div>
       ) : (
         <div className="space-y-2">
-          {samples?.map((sample) => (
-            <div
-              key={sample.id}
-              className="flex items-center justify-between p-3 border rounded-lg"
-            >
-              <div className="flex-1">
-                <p className="text-sm font-medium">{sample.reference_text}</p>
-                <p className="text-xs text-muted-foreground mt-1">{sample.audio_path}</p>
+          {samples?.map((sample, index) => {
+            const isEditing = editingSampleId === sample.id;
+
+            return (
+              <div
+                key={sample.id}
+                className={cn(
+                  'group relative rounded-lg border bg-card transition-all duration-200',
+                  isEditing ? 'ring-2 ring-primary/20' : 'hover:border-primary/30',
+                )}
+              >
+                {isEditing ? (
+                  /* Edit Mode */
+                  <div className="p-4 space-y-3">
+                    <div className="flex items-center gap-2 text-xs text-muted-foreground mb-2">
+                      <Edit className="h-3 w-3" />
+                      <span>Editing transcription</span>
+                    </div>
+                    <Textarea
+                      value={editedText}
+                      onChange={(e) => setEditedText(e.target.value)}
+                      className="min-h-[100px] text-sm resize-none"
+                      placeholder="Enter reference text..."
+                      autoFocus
+                    />
+                    <div className="flex items-center justify-end gap-2 pt-1">
+                      <Button
+                        type="button"
+                        size="sm"
+                        variant="ghost"
+                        onClick={handleCancelEdit}
+                        disabled={updateSample.isPending}
+                      >
+                        <X className="h-4 w-4 mr-1" />
+                        Cancel
+                      </Button>
+                      <Button
+                        type="button"
+                        size="sm"
+                        onClick={() => handleSaveEdit(sample.id)}
+                        disabled={updateSample.isPending}
+                      >
+                        <Check className="h-4 w-4 mr-1" />
+                        {updateSample.isPending ? 'Saving...' : 'Save'}
+                      </Button>
+                    </div>
+                  </div>
+                ) : (
+                  <>
+                    {/* View Mode */}
+                    <div className="flex items-center gap-3 p-3 h-[72px]">
+                      {/* Text Content */}
+                      <div className="flex-1 min-w-0 py-0.5">
+                        <p className="text-sm font-medium line-clamp-2 leading-snug">
+                          {sample.reference_text}
+                        </p>
+                      </div>
+
+                      {/* Action Buttons */}
+                      <div className="shrink-0 flex items-center gap-0.5 opacity-0 group-hover:opacity-100 transition-opacity">
+                        <CircleButton
+                          icon={Edit}
+                          title="Edit transcription"
+                          onClick={() => handleStartEdit(sample.id, sample.reference_text)}
+                        />
+                        <CircleButton
+                          icon={Trash2}
+                          title="Delete sample"
+                          onClick={() => handleDeleteClick(sample.id)}
+                          disabled={deleteSample.isPending}
+                        />
+                      </div>
+
+                      {/* Sample Number Badge */}
+                      <div className="absolute top-1 right-2 text-[10px] text-muted-foreground/50 font-medium">
+                        #{index + 1}
+                      </div>
+                    </div>
+
+                    {/* Mini Player - Always visible */}
+                    <MiniSamplePlayer audioUrl={apiClient.getSampleUrl(sample.id)} />
+                  </>
+                )}
               </div>
-              <div className="flex gap-2">
-                <Button
-                  type="button"
-                  variant="ghost"
-                  size="sm"
-                  onClick={() => handlePlay(sample.reference_text, sample.id)}
-                  className={currentAudioId === sample.id && isPlaying ? 'text-primary' : ''}
-                >
-                  <Play className="h-4 w-4 mr-1" />
-                  Play
-                </Button>
-                <Button
-                  type="button"
-                  variant="ghost"
-                  size="sm"
-                  onClick={() => handleDelete(sample.id)}
-                  disabled={deleteSample.isPending}
-                >
-                  <Trash2 className="h-4 w-4 text-destructive" />
-                </Button>
-              </div>
-            </div>
-          ))}
+            );
+          })}
         </div>
       )}
 
+      <Button
+        type="button"
+        variant="outline"
+        className="w-full"
+        onClick={() => setUploadOpen(true)}
+      >
+        <Plus className="mr-2 h-4 w-4" />
+        Add Sample
+      </Button>
+
+      <p className="text-xs text-muted-foreground text-center px-2">
+        Note: A single 30-second sample is the sweet spot. Quality may decrease with multiple
+        samples. In a future update samples might be interchangeable and tagged for varying styles
+        of the same voice.
+      </p>
+
       <SampleUpload profileId={profileId} open={uploadOpen} onOpenChange={setUploadOpen} />
+
+      <Dialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>Delete Sample</DialogTitle>
+            <DialogDescription>
+              Are you sure you want to delete this audio sample? This action cannot be undone.
+            </DialogDescription>
+          </DialogHeader>
+          <DialogFooter>
+            <Button
+              variant="outline"
+              onClick={() => {
+                setDeleteDialogOpen(false);
+                setSampleToDelete(null);
+              }}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="destructive"
+              onClick={handleDeleteConfirm}
+              disabled={deleteSample.isPending}
+            >
+              {deleteSample.isPending ? 'Deleting...' : 'Delete'}
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
     </div>
   );
 }

app/src/components/VoiceProfiles/SampleUpload.tsx

@@ -1,6 +1,6 @@
 import { zodResolver } from '@hookform/resolvers/zod';
 import { Mic, Monitor, Upload } from 'lucide-react';
-import { useState, useEffect } from 'react';
+import { useEffect, useState } from 'react';
 import { useForm } from 'react-hook-form';
 import * as z from 'zod';
 import { Button } from '@/components/ui/button';
@@ -27,7 +27,7 @@ import { useAudioRecording } from '@/lib/hooks/useAudioRecording';
 import { useAddSample, useProfile } from '@/lib/hooks/useProfiles';
 import { useSystemAudioCapture } from '@/lib/hooks/useSystemAudioCapture';
 import { useTranscription } from '@/lib/hooks/useTranscription';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 import { AudioSampleRecording } from './AudioSampleRecording';
 import { AudioSampleSystem } from './AudioSampleSystem';
 import { AudioSampleUpload } from './AudioSampleUpload';
@@ -49,6 +49,7 @@ interface SampleUploadProps {
 }
 
 export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProps) {
+  const platform = usePlatform();
   const addSample = useAddSample();
   const transcribe = useTranscription();
   const { data: profile } = useProfile(profileId);
@@ -73,7 +74,7 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
     stopRecording,
     cancelRecording,
   } = useAudioRecording({
-    maxDurationSeconds: 30,
+    maxDurationSeconds: 29,
     onRecordingComplete: (blob, recordedDuration) => {
       // Convert blob to File object
       const file = new File([blob], `recording-${Date.now()}.webm`, {
@@ -100,7 +101,7 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
     stopRecording: stopSystemRecording,
     cancelRecording: cancelSystemRecording,
   } = useSystemAudioCapture({
-    maxDurationSeconds: 30,
+    maxDurationSeconds: 29,
     onRecordingComplete: (blob, recordedDuration) => {
       // Convert blob to File object
       const file = new File([blob], `system-audio-${Date.now()}.wav`, {
@@ -232,7 +233,7 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
           <form onSubmit={form.handleSubmit(onSubmit)} className="space-y-4">
             <Tabs value={mode} onValueChange={(v) => setMode(v as 'upload' | 'record' | 'system')}>
               <TabsList
-                className={`grid w-full ${isTauri() && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
+                className={`grid w-full ${platform.metadata.isTauri && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
               >
                 <TabsTrigger value="upload" className="flex items-center gap-2">
                   <Upload className="h-4 w-4 shrink-0" />
@@ -242,7 +243,7 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
                   <Mic className="h-4 w-4 shrink-0" />
                   Record
                 </TabsTrigger>
-                {isTauri() && isSystemAudioSupported && (
+                {platform.metadata.isTauri && isSystemAudioSupported && (
                   <TabsTrigger value="system" className="flex items-center gap-2">
                     <Monitor className="h-4 w-4 shrink-0" />
                     System Audio
@@ -289,7 +290,7 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
                 />
               </TabsContent>
 
-              {isTauri() && isSystemAudioSupported && (
+              {platform.metadata.isTauri && isSystemAudioSupported && (
                 <TabsContent value="system" className="space-y-4">
                   <FormField
                     control={form.control}

app/src/components/ui/circle-button.tsx

@@ -6,10 +6,11 @@ export interface CircleButtonProps extends React.ButtonHTMLAttributes<HTMLButton
 }
 
 const CircleButton = React.forwardRef<HTMLButtonElement, CircleButtonProps>(
-  ({ className, icon: Icon, ...props }, ref) => {
+  ({ className, icon: Icon, type = 'button', ...props }, ref) => {
     return (
       <button
         ref={ref}
+        type={type}
         className={cn(
           'h-7 w-7 rounded-full flex items-center justify-center flex-shrink-0',
           'hover:bg-muted transition-colors',

app/src/components/ui/popover.tsx

@@ -0,0 +1,28 @@
+import * as PopoverPrimitive from '@radix-ui/react-popover';
+import * as React from 'react';
+import { cn } from '@/lib/utils/cn';
+
+const Popover = PopoverPrimitive.Root;
+
+const PopoverTrigger = PopoverPrimitive.Trigger;
+
+const PopoverContent = React.forwardRef<
+  React.ElementRef<typeof PopoverPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof PopoverPrimitive.Content>
+>(({ className, align = 'center', sideOffset = 4, ...props }, ref) => (
+  <PopoverPrimitive.Portal>
+    <PopoverPrimitive.Content
+      ref={ref}
+      align={align}
+      sideOffset={sideOffset}
+      className={cn(
+        'z-50 w-72 rounded-md border bg-popover p-4 text-popover-foreground shadow-md outline-none data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2',
+        className,
+      )}
+      {...props}
+    />
+  </PopoverPrimitive.Portal>
+));
+PopoverContent.displayName = PopoverPrimitive.Content.displayName;
+
+export { Popover, PopoverTrigger, PopoverContent };

app/src/global.d.ts

@@ -0,0 +1,3 @@
+interface Window {
+  __voiceboxServerStartedByApp?: boolean;
+}

app/src/hooks/useAutoUpdater.ts

@@ -1,172 +1,47 @@
-import { relaunch } from '@tauri-apps/plugin-process';
-import { check, type Update } from '@tauri-apps/plugin-updater';
-import { useCallback, useEffect, useState } from 'react';
+import { useCallback, useEffect, useRef, useState } from 'react';
+import { usePlatform } from '@/platform/PlatformContext';
+import type { UpdateStatus } from '@/platform/types';
 
-export interface UpdateStatus {
-  checking: boolean;
-  available: boolean;
-  version?: string;
-  downloading: boolean;
-  installing: boolean;
-  readyToInstall: boolean;
-  error?: string;
-  downloadProgress?: number; // 0-100 percentage
-  downloadedBytes?: number;
-  totalBytes?: number;
-}
-
-// Check if we're on Windows (NSIS installer handles restart automatically)
-const isWindows = () => {
-  return navigator.userAgent.includes('Windows');
-};
-
-const isTauri = () => {
-  return '__TAURI_INTERNALS__' in window;
-};
+// Re-export UpdateStatus for backwards compatibility
+export type { UpdateStatus };
 
 export function useAutoUpdater(checkOnMount = false) {
-  const [status, setStatus] = useState<UpdateStatus>({
-    checking: false,
-    available: false,
-    downloading: false,
-    installing: false,
-    readyToInstall: false,
-  });
+  const platform = usePlatform();
+  const [status, setStatus] = useState<UpdateStatus>(platform.updater.getStatus());
+  const hasCheckedRef = useRef(false);
 
-  const [update, setUpdate] = useState<Update | 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 () => {
-    if (!isTauri()) {
-      return;
-    }
+    await platform.updater.checkForUpdates();
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.checkForUpdates]);
 
-    try {
-      setStatus((prev) => ({ ...prev, checking: true, error: undefined }));
+  const downloadAndInstall = useCallback(async () => {
+    await platform.updater.downloadAndInstall();
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.downloadAndInstall]);
 
-      const foundUpdate = await check();
-
-      if (foundUpdate?.available) {
-        setUpdate(foundUpdate);
-        setStatus({
-          checking: false,
-          available: true,
-          version: foundUpdate.version,
-          downloading: false,
-          installing: false,
-          readyToInstall: false,
-        });
-      } else {
-        setStatus({
-          checking: false,
-          available: false,
-          downloading: false,
-          installing: false,
-          readyToInstall: false,
-        });
-      }
-    } catch (error) {
-      setStatus({
-        checking: false,
-        available: false,
-        downloading: false,
-        installing: false,
-        readyToInstall: false,
-        error: error instanceof Error ? error.message : 'Failed to check for updates',
-      });
-    }
-  }, []);
-
-  // Download the update (but don't install yet)
-  const downloadAndInstall = async () => {
-    if (!update || !isTauri()) return;
-
-    try {
-      setStatus((prev) => ({ ...prev, downloading: true, error: undefined }));
-
-      let downloadedBytes = 0;
-      let totalBytes = 0;
-
-      // Just download the update
-      await update.download((event) => {
-        switch (event.event) {
-          case 'Started':
-            totalBytes = event.data.contentLength || 0;
-            downloadedBytes = 0;
-            setStatus((prev) => ({
-              ...prev,
-              downloading: true,
-              totalBytes,
-              downloadedBytes: 0,
-              downloadProgress: 0,
-            }));
-            break;
-          case 'Progress': {
-            downloadedBytes += event.data.chunkLength;
-            const progress =
-              totalBytes > 0 ? Math.round((downloadedBytes / totalBytes) * 100) : undefined;
-            setStatus((prev) => ({
-              ...prev,
-              downloadedBytes,
-              downloadProgress: progress,
-            }));
-            break;
-          }
-          case 'Finished':
-            setStatus((prev) => ({
-              ...prev,
-              downloading: false,
-              readyToInstall: true,
-              downloadProgress: 100,
-            }));
-            break;
-        }
-      });
-    } catch (error) {
-      setStatus((prev) => ({
-        ...prev,
-        downloading: false,
-        installing: false,
-        readyToInstall: false,
-        downloadProgress: undefined,
-        downloadedBytes: undefined,
-        totalBytes: undefined,
-        error: error instanceof Error ? error.message : 'Failed to download update',
-      }));
-    }
-  };
-
-  // Install the downloaded update and restart the app
-  const restartAndInstall = async () => {
-    if (!update || !isTauri()) return;
-
-    try {
-      setStatus((prev) => ({ ...prev, installing: true, error: undefined }));
-
-      // Install the update
-      await update.install();
-
-      // On Windows with NSIS, the installer handles the restart automatically.
-      // The process will be killed by the NSIS installer, so we won't reach here.
-      // On macOS/Linux, we need to manually relaunch.
-      if (!isWindows()) {
-        await relaunch();
-      }
-      // If we're on Windows and somehow still running, the NSIS installer
-      // should have already handled everything. Just wait for the process to end.
-    } catch (error) {
-      setStatus((prev) => ({
-        ...prev,
-        installing: false,
-        error: error instanceof Error ? error.message : 'Failed to install update',
-      }));
-    }
-  };
+  const restartAndInstall = useCallback(async () => {
+    await platform.updater.restartAndInstall();
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.restartAndInstall]);
 
   useEffect(() => {
-    if (checkOnMount && isTauri()) {
+    if (checkOnMount && platform.metadata.isTauri && !hasCheckedRef.current) {
+      hasCheckedRef.current = true;
       checkForUpdates();
     }
-  }, [checkOnMount, checkForUpdates]);
+    // 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/lib/api/client.ts

@@ -1,4 +1,5 @@
 import { useServerStore } from '@/stores/serverStore';
+import type { LanguageCode } from '@/lib/constants/languages';
 import type {
   VoiceProfileCreate,
   VoiceProfileResponse,
@@ -13,6 +14,16 @@ import type {
   ModelStatusListResponse,
   ModelDownloadRequest,
   ActiveTasksResponse,
+  StoryCreate,
+  StoryResponse,
+  StoryDetailResponse,
+  StoryItemCreate,
+  StoryItemDetail,
+  StoryItemBatchUpdate,
+  StoryItemReorder,
+  StoryItemMove,
+  StoryItemTrim,
+  StoryItemSplit,
 } from './types';
 
 class ApiClient {
@@ -110,6 +121,16 @@ class ApiClient {
     });
   }
 
+  async updateProfileSample(
+    sampleId: string,
+    referenceText: string,
+  ): Promise<ProfileSampleResponse> {
+    return this.request<ProfileSampleResponse>(`/profiles/samples/${sampleId}`, {
+      method: 'PUT',
+      body: JSON.stringify({ reference_text: referenceText }),
+    });
+  }
+
   async exportProfile(profileId: string): Promise<Blob> {
     const url = `${this.getBaseUrl()}/profiles/${profileId}/export`;
     const response = await fetch(url);
@@ -144,6 +165,32 @@ class ApiClient {
     return response.json();
   }
 
+  async uploadAvatar(profileId: string, file: File): Promise<VoiceProfileResponse> {
+    const url = `${this.getBaseUrl()}/profiles/${profileId}/avatar`;
+    const formData = new FormData();
+    formData.append('file', file);
+
+    const response = await fetch(url, {
+      method: 'POST',
+      body: formData,
+    });
+
+    if (!response.ok) {
+      const error = await response.json().catch(() => ({
+        detail: response.statusText,
+      }));
+      throw new Error(error.detail || `HTTP error! status: ${response.status}`);
+    }
+
+    return response.json();
+  }
+
+  async deleteAvatar(profileId: string): Promise<void> {
+    await this.request<void>(`/profiles/${profileId}/avatar`, {
+      method: 'DELETE',
+    });
+  }
+
   // Generation
   async generateSpeech(data: GenerationRequest): Promise<GenerationResponse> {
     return this.request<GenerationResponse>('/generate', {
@@ -234,7 +281,7 @@ class ApiClient {
   }
 
   // Transcription
-  async transcribeAudio(file: File, language?: 'en' | 'zh'): Promise<TranscriptionResponse> {
+  async transcribeAudio(file: File, language?: LanguageCode): Promise<TranscriptionResponse> {
     const formData = new FormData();
     formData.append('file', file);
     if (language) {
@@ -263,10 +310,13 @@ class ApiClient {
   }
 
   async triggerModelDownload(modelName: string): Promise<{ message: string }> {
-    return this.request<{ message: string }>('/models/download', {
+    console.log('[API] triggerModelDownload called for:', modelName, 'at', new Date().toISOString());
+    const result = await this.request<{ message: string }>('/models/download', {
       method: 'POST',
       body: JSON.stringify({ model_name: modelName } as ModelDownloadRequest),
     });
+    console.log('[API] triggerModelDownload response:', result);
+    return result;
   }
 
   async deleteModel(modelName: string): Promise<{ message: string }> {
@@ -361,6 +411,103 @@ class ApiClient {
       body: JSON.stringify({ channel_ids: channelIds }),
     });
   }
+
+  // Stories
+  async listStories(): Promise<StoryResponse[]> {
+    return this.request<StoryResponse[]>('/stories');
+  }
+
+  async createStory(data: StoryCreate): Promise<StoryResponse> {
+    return this.request<StoryResponse>('/stories', {
+      method: 'POST',
+      body: JSON.stringify(data),
+    });
+  }
+
+  async getStory(storyId: string): Promise<StoryDetailResponse> {
+    return this.request<StoryDetailResponse>(`/stories/${storyId}`);
+  }
+
+  async updateStory(storyId: string, data: StoryCreate): Promise<StoryResponse> {
+    return this.request<StoryResponse>(`/stories/${storyId}`, {
+      method: 'PUT',
+      body: JSON.stringify(data),
+    });
+  }
+
+  async deleteStory(storyId: string): Promise<void> {
+    await this.request<void>(`/stories/${storyId}`, {
+      method: 'DELETE',
+    });
+  }
+
+  async addStoryItem(storyId: string, data: StoryItemCreate): Promise<StoryItemDetail> {
+    return this.request<StoryItemDetail>(`/stories/${storyId}/items`, {
+      method: 'POST',
+      body: JSON.stringify(data),
+    });
+  }
+
+  async removeStoryItem(storyId: string, itemId: string): Promise<void> {
+    await this.request<void>(`/stories/${storyId}/items/${itemId}`, {
+      method: 'DELETE',
+    });
+  }
+
+  async updateStoryItemTimes(storyId: string, data: StoryItemBatchUpdate): Promise<void> {
+    await this.request<void>(`/stories/${storyId}/items/times`, {
+      method: 'PUT',
+      body: JSON.stringify(data),
+    });
+  }
+
+  async reorderStoryItems(storyId: string, data: StoryItemReorder): Promise<StoryItemDetail[]> {
+    return this.request<StoryItemDetail[]>(`/stories/${storyId}/items/reorder`, {
+      method: 'PUT',
+      body: JSON.stringify(data),
+    });
+  }
+
+  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> {
+    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[]> {
+    return this.request<StoryItemDetail[]>(`/stories/${storyId}/items/${itemId}/split`, {
+      method: 'POST',
+      body: JSON.stringify(data),
+    });
+  }
+
+  async duplicateStoryItem(storyId: string, itemId: string): Promise<StoryItemDetail> {
+    return this.request<StoryItemDetail>(`/stories/${storyId}/items/${itemId}/duplicate`, {
+      method: 'POST',
+    });
+  }
+
+  async exportStoryAudio(storyId: string): Promise<Blob> {
+    const url = `${this.getBaseUrl()}/stories/${storyId}/export-audio`;
+    const response = await fetch(url);
+
+    if (!response.ok) {
+      const error = await response.json().catch(() => ({
+        detail: response.statusText,
+      }));
+      throw new Error(error.detail || `HTTP error! status: ${response.status}`);
+    }
+
+    return response.blob();
+  }
 }
 
 export const apiClient = new ApiClient();

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

@@ -1,9 +1,10 @@
 // API Types matching backend Pydantic models
+import type { LanguageCode } from '@/lib/constants/languages';
 
 export interface VoiceProfileCreate {
   name: string;
   description?: string;
-  language: 'en' | 'zh';
+  language: LanguageCode;
 }
 
 export interface VoiceProfileResponse {
@@ -11,6 +12,7 @@ export interface VoiceProfileResponse {
   name: string;
   description?: string;
   language: string;
+  avatar_path?: string;
   created_at: string;
   updated_at: string;
 }
@@ -29,7 +31,7 @@ export interface ProfileSampleResponse {
 export interface GenerationRequest {
   profile_id: string;
   text: string;
-  language: 'en' | 'zh';
+  language: LanguageCode;
   seed?: number;
   model_size?: '1.7B' | '0.6B';
 }
@@ -62,7 +64,7 @@ export interface HistoryListResponse {
 }
 
 export interface TranscriptionRequest {
-  language?: 'en' | 'zh';
+  language?: LanguageCode;
 }
 
 export interface TranscriptionResponse {
@@ -94,6 +96,7 @@ export interface ModelStatus {
   model_name: string;
   display_name: string;
   downloaded: boolean;
+  downloading: boolean;  // True if download is in progress
   size_mb?: number;
   loaded: boolean;
 }
@@ -123,3 +126,79 @@ export interface ActiveTasksResponse {
   downloads: ActiveDownloadTask[];
   generations: ActiveGenerationTask[];
 }
+
+export interface StoryCreate {
+  name: string;
+  description?: string;
+}
+
+export interface StoryResponse {
+  id: string;
+  name: string;
+  description?: string;
+  created_at: string;
+  updated_at: string;
+  item_count: number;
+}
+
+export interface StoryItemDetail {
+  id: string;
+  story_id: string;
+  generation_id: string;
+  start_time_ms: number;
+  track: number;
+  trim_start_ms: number;
+  trim_end_ms: number;
+  created_at: string;
+  profile_id: string;
+  profile_name: string;
+  text: string;
+  language: string;
+  audio_path: string;
+  duration: number;
+  seed?: number;
+  instruct?: string;
+  generation_created_at: string;
+}
+
+export interface StoryDetailResponse {
+  id: string;
+  name: string;
+  description?: string;
+  created_at: string;
+  updated_at: string;
+  items: StoryItemDetail[];
+}
+
+export interface StoryItemCreate {
+  generation_id: string;
+  start_time_ms?: number;
+  track?: number;
+}
+
+export interface StoryItemUpdateTime {
+  generation_id: string;
+  start_time_ms: number;
+}
+
+export interface StoryItemBatchUpdate {
+  updates: StoryItemUpdateTime[];
+}
+
+export interface StoryItemReorder {
+  generation_ids: string[];
+}
+
+export interface StoryItemMove {
+  start_time_ms: number;
+  track: number;
+}
+
+export interface StoryItemTrim {
+  trim_start_ms: number;
+  trim_end_ms: number;
+}
+
+export interface StoryItemSplit {
+  split_time_ms: number;
+}

app/src/lib/hooks/useAudioRecording.ts

@@ -1,5 +1,5 @@
 import { useCallback, useEffect, useRef, useState } from 'react';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 import { convertToWav } from '@/lib/utils/audio';
 
 interface UseAudioRecordingOptions {
@@ -8,9 +8,10 @@ interface UseAudioRecordingOptions {
 }
 
 export function useAudioRecording({
-  maxDurationSeconds = 30,
+  maxDurationSeconds = 29,
   onRecordingComplete,
 }: UseAudioRecordingOptions = {}) {
+  const platform = usePlatform();
   const [isRecording, setIsRecording] = useState(false);
   const [duration, setDuration] = useState(0);
   const [error, setError] = useState<string | null>(null);
@@ -40,15 +41,14 @@ export function useAudioRecording({
         await new Promise((resolve) => setTimeout(resolve, 100));
 
         if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
-          const isTauriEnv = isTauri();
           console.error('MediaDevices check:', {
             hasNavigator: typeof navigator !== 'undefined',
             hasMediaDevices: !!navigator?.mediaDevices,
             hasGetUserMedia: !!navigator?.mediaDevices?.getUserMedia,
-            isTauri: isTauriEnv,
+            isTauri: platform.metadata.isTauri,
           });
 
-          const errorMsg = isTauriEnv
+          const errorMsg = platform.metadata.isTauri
             ? 'Microphone access is not available. Please ensure:\n1. The app has microphone permissions in System Settings (macOS: System Settings > Privacy & Security > Microphone)\n2. You restart the app after granting permissions\n3. You are using Tauri v2 with a webview that supports getUserMedia'
             : 'Microphone access is not available. Please ensure you are using a secure context (HTTPS or localhost) and that your browser has microphone permissions enabled.';
           setError(errorMsg);

app/src/lib/hooks/useGenerationForm.ts

@@ -0,0 +1,122 @@
+import { zodResolver } from '@hookform/resolvers/zod';
+import { useState } from 'react';
+import { useForm } from 'react-hook-form';
+import * as z from 'zod';
+import { useToast } from '@/components/ui/use-toast';
+import { apiClient } from '@/lib/api/client';
+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';
+
+const generationSchema = z.object({
+  text: z.string().min(1, 'Text is required').max(5000),
+  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(),
+});
+
+export type GenerationFormValues = z.infer<typeof generationSchema>;
+
+interface UseGenerationFormOptions {
+  onSuccess?: (generationId: string) => void;
+  defaultValues?: Partial<GenerationFormValues>;
+}
+
+export function useGenerationForm(options: UseGenerationFormOptions = {}) {
+  const { toast } = useToast();
+  const generation = useGeneration();
+  const setAudioWithAutoPlay = usePlayerStore((state) => state.setAudioWithAutoPlay);
+  const setIsGenerating = useGenerationStore((state) => state.setIsGenerating);
+  const [downloadingModelName, setDownloadingModelName] = useState<string | null>(null);
+  const [downloadingDisplayName, setDownloadingDisplayName] = useState<string | null>(null);
+
+  useModelDownloadToast({
+    modelName: downloadingModelName || '',
+    displayName: downloadingDisplayName || '',
+    enabled: !!downloadingModelName,
+  });
+
+  const form = useForm<GenerationFormValues>({
+    resolver: zodResolver(generationSchema),
+    defaultValues: {
+      text: '',
+      language: 'en',
+      seed: undefined,
+      modelSize: '1.7B',
+      instruct: '',
+      ...options.defaultValues,
+    },
+  });
+
+  async function handleSubmit(
+    data: GenerationFormValues,
+    selectedProfileId: string | null,
+  ): Promise<void> {
+    if (!selectedProfileId) {
+      toast({
+        title: 'No profile selected',
+        description: 'Please select a voice profile from the cards above.',
+        variant: 'destructive',
+      });
+      return;
+    }
+
+    try {
+      setIsGenerating(true);
+
+      const modelName = `qwen-tts-${data.modelSize}`;
+      const displayName = data.modelSize === '1.7B' ? 'Qwen TTS 1.7B' : 'Qwen TTS 0.6B';
+
+      try {
+        const modelStatus = await apiClient.getModelStatus();
+        const model = modelStatus.models.find((m) => m.model_name === modelName);
+
+        if (model && !model.downloaded) {
+          setDownloadingModelName(modelName);
+          setDownloadingDisplayName(displayName);
+        }
+      } catch (error) {
+        console.error('Failed to check model status:', error);
+      }
+
+      const result = await generation.mutateAsync({
+        profile_id: selectedProfileId,
+        text: data.text,
+        language: data.language,
+        seed: data.seed,
+        model_size: data.modelSize,
+        instruct: data.instruct || undefined,
+      });
+
+      toast({
+        title: 'Generation complete!',
+        description: `Audio generated (${result.duration.toFixed(2)}s)`,
+      });
+
+      const audioUrl = apiClient.getAudioUrl(result.id);
+      setAudioWithAutoPlay(audioUrl, result.id, selectedProfileId, data.text.substring(0, 50));
+
+      form.reset();
+      options.onSuccess?.(result.id);
+    } catch (error) {
+      toast({
+        title: 'Generation failed',
+        description: error instanceof Error ? error.message : 'Failed to generate audio',
+        variant: 'destructive',
+      });
+    } finally {
+      setIsGenerating(false);
+      setDownloadingModelName(null);
+      setDownloadingDisplayName(null);
+    }
+  }
+
+  return {
+    form,
+    handleSubmit,
+    isPending: generation.isPending,
+  };
+}

app/src/lib/hooks/useHistory.ts

@@ -1,7 +1,7 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
 import { apiClient } from '@/lib/api/client';
 import type { HistoryQuery } from '@/lib/api/types';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 
 export function useHistory(query?: HistoryQuery) {
   return useQuery({
@@ -30,116 +30,52 @@ export function useDeleteGeneration() {
 }
 
 export function useExportGeneration() {
+  const platform = usePlatform();
+
   return useMutation({
     mutationFn: async ({ generationId, text }: { generationId: string; text: string }) => {
       const blob = await apiClient.exportGeneration(generationId);
-      
+
       // Create safe filename from text
-      const safeText = text.substring(0, 30).replace(/[^a-z0-9]/gi, '-').toLowerCase();
+      const safeText = text
+        .substring(0, 30)
+        .replace(/[^a-z0-9]/gi, '-')
+        .toLowerCase();
       const filename = `generation-${safeText}.voicebox.zip`;
-      
-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Voicebox Generation',
-                extensions: ['voicebox.zip', 'zip'],
-              },
-            ],
-          });
-          
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
-      
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Voicebox Generation',
+          extensions: ['zip'],
+        },
+      ]);
+
       return blob;
     },
   });
 }
 
 export function useExportGenerationAudio() {
+  const platform = usePlatform();
+
   return useMutation({
     mutationFn: async ({ generationId, text }: { generationId: string; text: string }) => {
       const blob = await apiClient.exportGenerationAudio(generationId);
-      
+
       // Create safe filename from text
-      const safeText = text.substring(0, 30).replace(/[^a-z0-9]/gi, '-').toLowerCase();
+      const safeText = text
+        .substring(0, 30)
+        .replace(/[^a-z0-9]/gi, '-')
+        .toLowerCase();
       const filename = `${safeText}.wav`;
-      
-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Audio File',
-                extensions: ['wav'],
-              },
-            ],
-          });
-          
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
-      
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Audio File',
+          extensions: ['wav'],
+        },
+      ]);
+
       return blob;
     },
   });

app/src/lib/hooks/useModelDownloadToast.tsx

@@ -1,14 +1,16 @@
-import { useEffect, useRef } from 'react';
-import { useToast } from '@/components/ui/use-toast';
-import { useServerStore } from '@/stores/serverStore';
+import { CheckCircle2, Loader2, XCircle } from 'lucide-react';
+import { useCallback, useEffect, useRef } from 'react';
 import { Progress } from '@/components/ui/progress';
-import { Loader2, CheckCircle2, XCircle } from 'lucide-react';
+import { useToast } from '@/components/ui/use-toast';
 import type { ModelProgress } from '@/lib/api/types';
+import { useServerStore } from '@/stores/serverStore';
 
 interface UseModelDownloadToastOptions {
   modelName: string;
   displayName: string;
   enabled?: boolean;
+  onComplete?: () => void;
+  onError?: () => void;
 }
 
 /**
@@ -19,47 +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<
-    ((props: {
-      title?: React.ReactNode;
-      description?: React.ReactNode;
-      duration?: number;
-      variant?: 'default' | 'destructive';
-      open?: boolean;
-    }) => void) | null
-  >(null);
+  // biome-ignore lint: Using any for toast update ref to handle complex toast types
+  const toastUpdateRef = useRef<any>(null);
   const eventSourceRef = useRef<EventSource | null>(null);
 
-  const formatBytes = (bytes: number): string => {
+  const formatBytes = useCallback((bytes: number): string => {
     if (bytes === 0) return '0 B';
     const k = 1024;
     const sizes = ['B', 'KB', 'MB', 'GB'];
     const i = Math.floor(Math.log(bytes) / Math.log(k));
-    return `${(bytes / Math.pow(k, i)).toFixed(1)} ${sizes[i]}`;
-  };
+    return `${(bytes / k ** i).toFixed(1)} ${sizes[i]}`;
+  }, []);
 
   useEffect(() => {
+    console.log('[useModelDownloadToast] useEffect triggered', {
+      enabled,
+      serverUrl,
+      modelName,
+      displayName,
+    });
+
     if (!enabled || !serverUrl || !modelName) {
+      console.log('[useModelDownloadToast] Not enabled, skipping');
       return;
     }
 
+    console.log('[useModelDownloadToast] Creating toast and EventSource for:', modelName);
+
     // Create initial toast
     const toastResult = toast({
       title: displayName,
-      description: 'Starting download...',
+      description: (
+        <div className="flex items-center gap-2">
+          <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;
 
@@ -86,7 +105,7 @@ export function useModelDownloadToast({
               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" />;
@@ -117,21 +136,40 @@ export function useModelDownloadToast({
           });
 
           // Close connection and dismiss toast on completion or error
-          if (progress.status === 'complete' || progress.status === 'error') {
+          // Also treat progress >= 100% as complete
+          const isComplete = progress.status === 'complete' || progress.progress >= 100;
+          const isError = progress.status === 'error';
+
+          if (isComplete || isError) {
+            console.log('[useModelDownloadToast] Download finished:', {
+              isComplete,
+              isError,
+              progress: progress.progress,
+            });
             eventSource.close();
             eventSourceRef.current = null;
 
-            // Auto-dismiss on completion after delay
-            if (progress.status === 'complete') {
-              setTimeout(() => {
-                if (toastIdRef.current && toastUpdateRef.current) {
-                  toastUpdateRef.current({
-                    open: false,
-                  });
-                  toastIdRef.current = null;
-                  toastUpdateRef.current = null;
-                }
-              }, 5000);
+            // Update toast to show completion state before callbacks
+            if (isComplete && toastUpdateRef.current) {
+              toastUpdateRef.current({
+                title: (
+                  <div className="flex items-center gap-2">
+                    <CheckCircle2 className="h-4 w-4 text-green-500" />
+                    <span>{displayName}</span>
+                  </div>
+                ),
+                description: 'Download complete',
+                duration: 3000,
+              });
+            }
+
+            // Call callbacks
+            if (isComplete && onComplete) {
+              console.log('[useModelDownloadToast] Download complete, calling onComplete callback');
+              onComplete();
+            } else if (isError && onError) {
+              console.log('[useModelDownloadToast] Download error, calling onError callback');
+              onError();
             }
           }
         }
@@ -140,8 +178,9 @@ export function useModelDownloadToast({
       }
     };
 
-    eventSource.onerror = () => {
-      console.error('SSE error');
+    eventSource.onerror = (error) => {
+      console.error('[useModelDownloadToast] SSE error for:', modelName, error);
+      console.log('[useModelDownloadToast] EventSource readyState:', eventSource.readyState);
       eventSource.close();
       eventSourceRef.current = null;
 
@@ -162,15 +201,16 @@ 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/useProfiles.ts

@@ -1,7 +1,7 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
 import { apiClient } from '@/lib/api/client';
 import type { VoiceProfileCreate } from '@/lib/api/types';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 
 export function useProfiles() {
   return useQuery({
@@ -98,60 +98,43 @@ export function useDeleteSample() {
   });
 }
 
+export function useUpdateSample() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ sampleId, referenceText }: { sampleId: string; referenceText: string }) =>
+      apiClient.updateProfileSample(sampleId, referenceText),
+    onSuccess: (data) => {
+      queryClient.invalidateQueries({
+        queryKey: ['profiles', data.profile_id, 'samples'],
+      });
+      queryClient.invalidateQueries({
+        queryKey: ['profiles', data.profile_id],
+      });
+      queryClient.invalidateQueries({ queryKey: ['profiles'] });
+    },
+  });
+}
+
 export function useExportProfile() {
+  const platform = usePlatform();
+
   return useMutation({
     mutationFn: async (profileId: string) => {
       const blob = await apiClient.exportProfile(profileId);
-      
+
       // Get profile name for filename
       const profile = await apiClient.getProfile(profileId);
       const safeName = profile.name.replace(/[^a-z0-9]/gi, '-').toLowerCase();
       const filename = `profile-${safeName}.voicebox.zip`;
-      
-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Voicebox Profile',
-                extensions: ['voicebox.zip', 'zip'],
-              },
-            ],
-          });
-          
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
-      
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Voicebox Profile',
+          extensions: ['zip'],
+        },
+      ]);
+
       return blob;
     },
   });
@@ -167,3 +150,32 @@ export function useImportProfile() {
     },
   });
 }
+
+export function useUploadAvatar() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ profileId, file }: { profileId: string; file: File }) =>
+      apiClient.uploadAvatar(profileId, file),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['profiles'] });
+      queryClient.invalidateQueries({
+        queryKey: ['profiles', variables.profileId],
+      });
+    },
+  });
+}
+
+export function useDeleteAvatar() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: (profileId: string) => apiClient.deleteAvatar(profileId),
+    onSuccess: (_, profileId) => {
+      queryClient.invalidateQueries({ queryKey: ['profiles'] });
+      queryClient.invalidateQueries({
+        queryKey: ['profiles', profileId],
+      });
+    },
+  });
+}

app/src/lib/hooks/useStories.ts

@@ -0,0 +1,181 @@
+import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
+import { apiClient } from '@/lib/api/client';
+import type { StoryCreate, StoryItemCreate, StoryItemBatchUpdate, StoryItemReorder, StoryItemMove, StoryItemTrim, StoryItemSplit } from '@/lib/api/types';
+import { usePlatform } from '@/platform/PlatformContext';
+
+export function useStories() {
+  return useQuery({
+    queryKey: ['stories'],
+    queryFn: () => apiClient.listStories(),
+  });
+}
+
+export function useStory(storyId: string | null) {
+  return useQuery({
+    queryKey: ['stories', storyId],
+    queryFn: () => apiClient.getStory(storyId!),
+    enabled: !!storyId,
+  });
+}
+
+export function useCreateStory() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: (data: StoryCreate) => apiClient.createStory(data),
+    onSuccess: () => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+    },
+  });
+}
+
+export function useUpdateStory() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, data }: { storyId: string; data: StoryCreate }) =>
+      apiClient.updateStory(storyId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useDeleteStory() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: (storyId: string) => apiClient.deleteStory(storyId),
+    onSuccess: () => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+    },
+  });
+}
+
+export function useAddStoryItem() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, data }: { storyId: string; data: StoryItemCreate }) =>
+      apiClient.addStoryItem(storyId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useRemoveStoryItem() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, itemId }: { storyId: string; itemId: string }) =>
+      apiClient.removeStoryItem(storyId, itemId),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useUpdateStoryItemTimes() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, data }: { storyId: string; data: StoryItemBatchUpdate }) =>
+      apiClient.updateStoryItemTimes(storyId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useReorderStoryItems() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, data }: { storyId: string; data: StoryItemReorder }) =>
+      apiClient.reorderStoryItems(storyId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useMoveStoryItem() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, itemId, data }: { storyId: string; itemId: string; data: StoryItemMove }) =>
+      apiClient.moveStoryItem(storyId, itemId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useTrimStoryItem() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, itemId, data }: { storyId: string; itemId: string; data: StoryItemTrim }) =>
+      apiClient.trimStoryItem(storyId, itemId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useSplitStoryItem() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, itemId, data }: { storyId: string; itemId: string; data: StoryItemSplit }) =>
+      apiClient.splitStoryItem(storyId, itemId, data),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useDuplicateStoryItem() {
+  const queryClient = useQueryClient();
+
+  return useMutation({
+    mutationFn: ({ storyId, itemId }: { storyId: string; itemId: string }) =>
+      apiClient.duplicateStoryItem(storyId, itemId),
+    onSuccess: (_, variables) => {
+      queryClient.invalidateQueries({ queryKey: ['stories'] });
+      queryClient.invalidateQueries({ queryKey: ['stories', variables.storyId] });
+    },
+  });
+}
+
+export function useExportStoryAudio() {
+  const platform = usePlatform();
+
+  return useMutation({
+    mutationFn: async ({ storyId, storyName }: { storyId: string; storyName: string }) => {
+      const blob = await apiClient.exportStoryAudio(storyId);
+
+      // Create safe filename
+      const safeName = storyName.substring(0, 50).replace(/[^a-z0-9]/gi, '-').toLowerCase();
+      const filename = `${safeName || 'story'}.wav`;
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Audio File',
+          extensions: ['wav'],
+        },
+      ]);
+
+      return blob;
+    },
+  });
+}

app/src/lib/hooks/useStoryPlayback.ts

@@ -0,0 +1,389 @@
+import { useCallback, useEffect, useRef } from 'react';
+import { apiClient } from '@/lib/api/client';
+import type { StoryItemDetail } from '@/lib/api/types';
+import { useStoryStore } from '@/stores/storyStore';
+
+interface ActiveSource {
+  source: AudioBufferSourceNode;
+  itemId: string;
+  generationId: string;
+  startTimeMs: number;
+  endTimeMs: number;
+}
+
+/**
+ * Hook for managing timecode-based story playback using Web Audio API.
+ * Supports multiple simultaneous audio sources for overlapping clips on different tracks.
+ * Uses AudioContext for sample-accurate timing synchronization.
+ */
+export function useStoryPlayback(items: StoryItemDetail[] | undefined) {
+  const isPlaying = useStoryStore((state) => state.isPlaying);
+  const playbackItems = useStoryStore((state) => state.playbackItems);
+  const playbackStartContextTime = useStoryStore((state) => state.playbackStartContextTime);
+  const playbackStartStoryTime = useStoryStore((state) => state.playbackStartStoryTime);
+  const setPlaybackTiming = useStoryStore((state) => state.setPlaybackTiming);
+
+  // AudioContext instance (created once)
+  const audioContextRef = useRef<AudioContext | null>(null);
+  // Master gain for volume control
+  const masterGainRef = useRef<GainNode | null>(null);
+  // Preloaded AudioBuffers by generation_id (audio file is shared between split clips)
+  const audioBuffersRef = useRef<Map<string, AudioBuffer>>(new Map());
+  // Currently playing AudioBufferSourceNodes by item.id (unique per clip)
+  const activeSourcesRef = useRef<Map<string, ActiveSource>>(new Map());
+  // Animation frame for syncing visual playhead
+  const animationFrameRef = useRef<number | null>(null);
+
+  // Get or create AudioContext and audio graph
+  const getAudioContext = useCallback(() => {
+    if (!audioContextRef.current) {
+      audioContextRef.current = new AudioContext();
+      console.log(
+        '[StoryPlayback] Created AudioContext, sample rate:',
+        audioContextRef.current.sampleRate,
+      );
+
+      // Create master gain node for volume control
+      masterGainRef.current = audioContextRef.current.createGain();
+      masterGainRef.current.gain.value = 1;
+      masterGainRef.current.connect(audioContextRef.current.destination);
+    }
+    // Resume context if suspended (browser autoplay policy)
+    if (audioContextRef.current.state === 'suspended') {
+      audioContextRef.current.resume().catch(() => {
+        // Ignore resume errors
+      });
+    }
+    return audioContextRef.current;
+  }, []);
+
+  // Stop a source by item id
+  const stopSource = useCallback((itemId: string) => {
+    const activeSource = activeSourcesRef.current.get(itemId);
+    if (activeSource) {
+      try {
+        activeSource.source.stop();
+      } catch {
+        // Source may have already stopped
+      }
+      activeSourcesRef.current.delete(itemId);
+    }
+  }, []);
+
+  // Preload audio files as AudioBuffers
+  useEffect(() => {
+    if (!items || items.length === 0) {
+      // Clear preloaded buffers when no items
+      audioBuffersRef.current.clear();
+      return;
+    }
+
+    const currentIds = new Set(items.map((item) => item.generation_id));
+    const audioContext = getAudioContext();
+
+    // Remove buffers for items that no longer exist
+    for (const [id] of audioBuffersRef.current) {
+      if (!currentIds.has(id)) {
+        audioBuffersRef.current.delete(id);
+      }
+    }
+
+    // Preload audio for new items
+    const preloadPromises: Promise<void>[] = [];
+    for (const item of items) {
+      if (!audioBuffersRef.current.has(item.generation_id)) {
+        const audioUrl = apiClient.getAudioUrl(item.generation_id);
+        console.log('[StoryPlayback] Preloading audio buffer:', item.generation_id);
+
+        const preloadPromise = fetch(audioUrl)
+          .then((response) => response.arrayBuffer())
+          .then((arrayBuffer) => audioContext.decodeAudioData(arrayBuffer))
+          .then((audioBuffer) => {
+            audioBuffersRef.current.set(item.generation_id, audioBuffer);
+            console.log(
+              '[StoryPlayback] Preloaded buffer:',
+              item.generation_id,
+              'duration:',
+              audioBuffer.duration,
+            );
+          })
+          .catch((err) => {
+            console.error('[StoryPlayback] Failed to preload audio:', item.generation_id, err);
+          });
+
+        preloadPromises.push(preloadPromise);
+      }
+    }
+
+    Promise.all(preloadPromises).then(() => {
+      console.log('[StoryPlayback] Preloaded', audioBuffersRef.current.size, 'audio buffers');
+    });
+  }, [items, getAudioContext]);
+
+  // Cleanup AudioContext on unmount
+  useEffect(() => {
+    return () => {
+      // Stop all sources
+      for (const [itemId] of activeSourcesRef.current) {
+        stopSource(itemId);
+      }
+      activeSourcesRef.current.clear();
+
+      // Clean up audio graph
+      if (masterGainRef.current) {
+        masterGainRef.current.disconnect();
+        masterGainRef.current = null;
+      }
+      if (audioContextRef.current && audioContextRef.current.state !== 'closed') {
+        audioContextRef.current.close().catch(() => {
+          // Ignore errors when closing
+        });
+        audioContextRef.current = null;
+      }
+
+      if (animationFrameRef.current !== null) {
+        cancelAnimationFrame(animationFrameRef.current);
+      }
+    };
+  }, [stopSource]);
+
+  // Find ALL items that should be playing at a given story time
+  const findActiveItems = useCallback(
+    (storyTimeMs: number, itemList: StoryItemDetail[]): StoryItemDetail[] => {
+      return itemList.filter((item) => {
+        const itemStart = item.start_time_ms;
+        // Use effective duration (accounting for trims)
+        const trimStartMs = item.trim_start_ms || 0;
+        const trimEndMs = item.trim_end_ms || 0;
+        const effectiveDurationMs = item.duration * 1000 - trimStartMs - trimEndMs;
+        const itemEnd = item.start_time_ms + effectiveDurationMs;
+        return storyTimeMs >= itemStart && storyTimeMs < itemEnd;
+      });
+    },
+    [],
+  );
+
+  // Convert AudioContext time to story time (ms)
+  const contextTimeToStoryTime = useCallback(
+    (contextTime: number): number => {
+      if (playbackStartContextTime === null || playbackStartStoryTime === null) {
+        return 0;
+      }
+      const elapsedContextTime = contextTime - playbackStartContextTime;
+      return playbackStartStoryTime + elapsedContextTime * 1000;
+    },
+    [playbackStartContextTime, playbackStartStoryTime],
+  );
+
+  // Convert story time (ms) to AudioContext time
+  const storyTimeToContextTime = useCallback(
+    (storyTimeMs: number): number => {
+      if (playbackStartContextTime === null || playbackStartStoryTime === null) {
+        return 0;
+      }
+      const elapsedStoryTime = (storyTimeMs - playbackStartStoryTime) / 1000;
+      return playbackStartContextTime + elapsedStoryTime;
+    },
+    [playbackStartContextTime, playbackStartStoryTime],
+  );
+
+  // Stop all sources
+  const stopAllSources = useCallback(() => {
+    console.log('[StoryPlayback] Stopping all sources');
+    for (const [itemId] of activeSourcesRef.current) {
+      stopSource(itemId);
+    }
+    activeSourcesRef.current.clear();
+  }, [stopSource]);
+
+  // Schedule playback for all items that should be playing
+  const schedulePlayback = useCallback(
+    (storyTimeMs: number, itemList: StoryItemDetail[]) => {
+      const audioContext = getAudioContext();
+      const currentContextTime = audioContext.currentTime;
+
+      // Find all items that should be playing
+      const shouldBePlaying = findActiveItems(storyTimeMs, itemList);
+      const shouldBePlayingIds = new Set(shouldBePlaying.map((item) => item.id));
+
+      // Stop sources that shouldn't be playing anymore
+      for (const [itemId] of activeSourcesRef.current) {
+        if (!shouldBePlayingIds.has(itemId)) {
+          stopSource(itemId);
+        }
+      }
+
+      // Schedule new sources for items that should be playing
+      for (const item of shouldBePlaying) {
+        if (!activeSourcesRef.current.has(item.id)) {
+          const buffer = audioBuffersRef.current.get(item.generation_id);
+          if (!buffer) {
+            console.warn('[StoryPlayback] Buffer not loaded for:', item.generation_id);
+            continue;
+          }
+
+          // Calculate when this item should start in AudioContext time
+          const itemStartContextTime = storyTimeToContextTime(item.start_time_ms);
+          
+          // Calculate effective duration and trim offsets
+          const trimStartSec = (item.trim_start_ms || 0) / 1000;
+          const trimEndSec = (item.trim_end_ms || 0) / 1000;
+          const effectiveDuration = item.duration - trimStartSec - trimEndSec;
+          const itemEndStoryTime = item.start_time_ms + effectiveDuration * 1000;
+
+          // Calculate offset into the buffer (if seeking mid-way)
+          // Offset is relative to the trimmed start of the clip
+          const offsetIntoEffectiveClip = Math.max(0, (storyTimeMs - item.start_time_ms) / 1000);
+          const offsetIntoBuffer = trimStartSec + offsetIntoEffectiveClip;
+          const duration = effectiveDuration - offsetIntoEffectiveClip;
+
+          // If the item should have already started, schedule it to start immediately
+          const startAtContextTime = Math.max(currentContextTime, itemStartContextTime);
+
+          console.log('[StoryPlayback] Scheduling source:', {
+            itemId: item.id,
+            generationId: item.generation_id,
+            storyTimeMs,
+            itemStart: item.start_time_ms,
+            offsetIntoBuffer,
+            startAtContextTime,
+            duration,
+          });
+
+          const source = audioContext.createBufferSource();
+          source.buffer = buffer;
+          source.connect(masterGainRef.current || audioContext.destination);
+
+          const activeSource: ActiveSource = {
+            source,
+            itemId: item.id,
+            generationId: item.generation_id,
+            startTimeMs: item.start_time_ms,
+            endTimeMs: itemEndStoryTime,
+          };
+
+          activeSourcesRef.current.set(item.id, activeSource);
+
+          // Schedule playback
+          source.start(startAtContextTime, offsetIntoBuffer, duration);
+
+          // Clean up when source ends
+          source.onended = () => {
+            console.log('[StoryPlayback] Source ended:', item.id);
+            activeSourcesRef.current.delete(item.id);
+          };
+        }
+      }
+    },
+    [getAudioContext, findActiveItems, storyTimeToContextTime, stopSource],
+  );
+
+  // Sync visual playhead from AudioContext time
+  useEffect(() => {
+    if (!isPlaying || playbackStartContextTime === null || playbackStartStoryTime === null) {
+      if (animationFrameRef.current !== null) {
+        cancelAnimationFrame(animationFrameRef.current);
+        animationFrameRef.current = null;
+      }
+      return;
+    }
+
+    const audioContext = getAudioContext();
+    const itemList = playbackItems || [];
+
+    const syncPlayhead = () => {
+      if (!useStoryStore.getState().isPlaying) {
+        return;
+      }
+
+      const currentContextTime = audioContext.currentTime;
+      const currentStoryTime = contextTimeToStoryTime(currentContextTime);
+      const totalDuration = useStoryStore.getState().totalDurationMs;
+
+      // Update store with current story time
+      useStoryStore.setState({ currentTimeMs: Math.min(currentStoryTime, totalDuration) });
+
+      // Schedule any items that should be playing
+      schedulePlayback(currentStoryTime, itemList);
+
+      // Check if we've reached the end
+      if (currentStoryTime >= totalDuration) {
+        // Check if all sources have ended
+        if (activeSourcesRef.current.size === 0) {
+          console.log('[StoryPlayback] Reached end');
+          useStoryStore.getState().stop();
+          return;
+        }
+      }
+
+      // Continue sync loop
+      animationFrameRef.current = requestAnimationFrame(syncPlayhead);
+    };
+
+    // Initial sync
+    const currentContextTime = audioContext.currentTime;
+    const currentStoryTime = contextTimeToStoryTime(currentContextTime);
+    schedulePlayback(currentStoryTime, itemList);
+
+    // Start sync loop
+    animationFrameRef.current = requestAnimationFrame(syncPlayhead);
+
+    return () => {
+      if (animationFrameRef.current !== null) {
+        cancelAnimationFrame(animationFrameRef.current);
+        animationFrameRef.current = null;
+      }
+    };
+  }, [
+    isPlaying,
+    playbackItems,
+    playbackStartContextTime,
+    playbackStartStoryTime,
+    getAudioContext,
+    contextTimeToStoryTime,
+    schedulePlayback,
+  ]);
+
+  // Handle play/pause changes - stop sources when paused
+  useEffect(() => {
+    if (!isPlaying) {
+      console.log('[StoryPlayback] Stopping playback');
+      stopAllSources();
+    }
+  }, [isPlaying, stopAllSources]);
+
+  // Handle seek - reset timing anchors when they become null (triggered by seek)
+  useEffect(() => {
+    if (!isPlaying || !playbackItems || playbackItems.length === 0) {
+      return;
+    }
+
+    // Only run when timing anchors are null (after a seek)
+    if (playbackStartContextTime !== null && playbackStartStoryTime !== null) {
+      return;
+    }
+
+    const audioContext = getAudioContext();
+    const currentContextTime = audioContext.currentTime;
+    const currentStoryTime = useStoryStore.getState().currentTimeMs;
+
+    console.log('[StoryPlayback] Setting timing anchors after seek:', {
+      contextTime: currentContextTime,
+      storyTime: currentStoryTime,
+    });
+    setPlaybackTiming(currentContextTime, currentStoryTime);
+
+    // Stop all existing sources and reschedule from new position
+    stopAllSources();
+    schedulePlayback(currentStoryTime, playbackItems);
+  }, [
+    isPlaying,
+    playbackItems,
+    playbackStartContextTime,
+    playbackStartStoryTime,
+    getAudioContext,
+    stopAllSources,
+    schedulePlayback,
+    setPlaybackTiming,
+  ]);
+}

app/src/lib/hooks/useSystemAudioCapture.ts

@@ -1,6 +1,5 @@
 import { useState, useRef, useCallback, useEffect } from 'react';
-import { invoke } from '@tauri-apps/api/core';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 
 interface UseSystemAudioCaptureOptions {
   maxDurationSeconds?: number;
@@ -12,9 +11,10 @@ interface UseSystemAudioCaptureOptions {
  * Uses ScreenCaptureKit on macOS and WASAPI loopback on Windows.
  */
 export function useSystemAudioCapture({
-  maxDurationSeconds = 30,
+  maxDurationSeconds = 29,
   onRecordingComplete,
 }: UseSystemAudioCaptureOptions = {}) {
+  const platform = usePlatform();
   const [isRecording, setIsRecording] = useState(false);
   const [duration, setDuration] = useState(0);
   const [error, setError] = useState<string | null>(null);
@@ -26,22 +26,12 @@ export function useSystemAudioCapture({
 
   // Check if system audio capture is supported
   useEffect(() => {
-    if (!isTauri()) {
-      setIsSupported(false);
-      return;
-    }
-
-    invoke<boolean>('is_system_audio_supported')
-      .then((supported) => {
-        setIsSupported(supported);
-      })
-      .catch(() => {
-        setIsSupported(false);
-      });
-  }, []);
+    const supported = platform.audio.isSystemAudioSupported();
+    setIsSupported(supported);
+  }, [platform]);
 
   const startRecording = useCallback(async () => {
-    if (!isTauri()) {
+    if (!platform.metadata.isTauri) {
       const errorMsg = 'System audio capture is only available in the desktop app.';
       setError(errorMsg);
       return;
@@ -58,9 +48,7 @@ export function useSystemAudioCapture({
       setDuration(0);
 
       // Start native capture
-      await invoke('start_system_audio_capture', {
-        maxDurationSecs: maxDurationSeconds,
-      });
+      await platform.audio.startSystemAudioCapture(maxDurationSeconds);
 
       setIsRecording(true);
       isRecordingRef.current = true;
@@ -86,10 +74,10 @@ export function useSystemAudioCapture({
       setError(errorMessage);
       setIsRecording(false);
     }
-  }, [maxDurationSeconds, isSupported]);
+  }, [maxDurationSeconds, isSupported, platform]);
 
   const stopRecording = useCallback(async () => {
-    if (!isRecording || !isTauri()) {
+    if (!isRecording || !platform.metadata.isTauri) {
       return;
     }
 
@@ -102,17 +90,9 @@ export function useSystemAudioCapture({
         timerRef.current = null;
       }
 
-      // Stop capture and get base64 WAV data
-      const base64Data = await invoke<string>('stop_system_audio_capture');
+      // Stop capture and get Blob
+      const blob = await platform.audio.stopSystemAudioCapture();
 
-      // Convert base64 to Blob
-      const binaryString = atob(base64Data);
-      const bytes = new Uint8Array(binaryString.length);
-      for (let i = 0; i < binaryString.length; i++) {
-        bytes[i] = binaryString.charCodeAt(i);
-      }
-
-      const blob = new Blob([bytes], { type: 'audio/wav' });
       // Pass the actual recorded duration
       const recordedDuration = startTimeRef.current 
         ? (Date.now() - startTimeRef.current) / 1000 
@@ -125,7 +105,7 @@ export function useSystemAudioCapture({
           : 'Failed to stop system audio capture.';
       setError(errorMessage);
     }
-  }, [isRecording, onRecordingComplete]);
+  }, [isRecording, onRecordingComplete, platform]);
 
   // Store stopRecording in ref for use in timer
   useEffect(() => {
@@ -155,15 +135,15 @@ export function useSystemAudioCapture({
         timerRef.current = null;
       }
       // Cancel recording on unmount if still recording
-      if (isRecordingRef.current && isTauri()) {
+      if (isRecordingRef.current && platform.metadata.isTauri) {
         // Call stop directly without the callback to avoid stale closure
-        invoke('stop_system_audio_capture').catch((err) => {
+        platform.audio.stopSystemAudioCapture().catch((err) => {
           console.error('Error stopping audio capture on unmount:', err);
         });
       }
     };
     // biome-ignore lint/correctness/useExhaustiveDependencies: Only run on unmount
-  }, []);
+  }, [platform]);
 
   return {
     isRecording,

app/src/lib/hooks/useTranscription.ts

@@ -1,9 +1,10 @@
 import { useMutation } from '@tanstack/react-query';
 import { apiClient } from '@/lib/api/client';
+import type { LanguageCode } from '@/lib/constants/languages';
 
 export function useTranscription() {
   return useMutation({
-    mutationFn: ({ file, language }: { file: File; language?: 'en' | 'zh' }) =>
+    mutationFn: ({ file, language }: { file: File; language?: LanguageCode }) =>
       apiClient.transcribeAudio(file, language),
   });
 }

app/src/lib/tauri.ts

@@ -1,108 +0,0 @@
-/**
- * Tauri integration utilities
- */
-
-import { invoke } from '@tauri-apps/api/core';
-import { listen, emit } from '@tauri-apps/api/event';
-
-/**
- * Check if running in Tauri environment
- */
-export function isTauri(): boolean {
-  return '__TAURI_INTERNALS__' in window;
-}
-
-/**
- * Check if running on macOS
- */
-export function isMacOS(): boolean {
-  return navigator.platform.toLowerCase().includes('mac');
-}
-
-/**
- * Start the bundled Python server (Tauri only)
- */
-export async function startServer(remote = false): Promise<string> {
-  if (!isTauri()) {
-    throw new Error('Not running in Tauri environment');
-  }
-
-  try {
-    const result = await invoke<string>('start_server', { remote });
-    console.log('Server started:', result);
-    return result;
-  } catch (error) {
-    console.error('Failed to start server:', error);
-    throw error;
-  }
-}
-
-/**
- * Stop the bundled Python server (Tauri only)
- */
-export async function stopServer(): Promise<void> {
-  if (!isTauri()) {
-    throw new Error('Not running in Tauri environment');
-  }
-
-  try {
-    await invoke('stop_server');
-    console.log('Server stopped');
-  } catch (error) {
-    console.error('Failed to stop server:', error);
-    throw error;
-  }
-}
-
-/**
- * Set whether the server should keep running when the app closes (Tauri only)
- */
-export async function setKeepServerRunning(keepRunning: boolean): Promise<void> {
-  if (!isTauri()) {
-    return;
-  }
-
-  try {
-    await invoke('set_keep_server_running', { keepRunning });
-  } catch (error) {
-    console.error('Failed to set keep server running setting:', error);
-  }
-}
-
-/**
- * Setup window close handler to check setting and stop server if needed
- */
-export async function setupWindowCloseHandler(): Promise<void> {
-  if (!isTauri()) {
-    return;
-  }
-
-  try {
-    // Listen for window close request from Rust
-    await listen<null>('window-close-requested', async () => {
-      // Import store here to avoid circular dependency
-      const { useServerStore } = await import('@/stores/serverStore');
-      const keepRunning = useServerStore.getState().keepServerRunningOnClose;
-
-      // Check if server was started by this app instance
-      // In dev mode, serverStartedByApp will be false, so we won't try to stop a separately-run server
-      // We need to access the module-level variable - this is a bit hacky but works
-      // @ts-expect-error - accessing module-level variable from another module
-      const serverStartedByApp = window.__voiceboxServerStartedByApp ?? false;
-
-      if (!keepRunning && serverStartedByApp) {
-        // Stop server before closing (only if we started it)
-        try {
-          await stopServer();
-        } catch (error) {
-          console.error('Failed to stop server on close:', error);
-        }
-      }
-
-      // Emit event back to Rust to allow close
-      await emit('window-close-allowed');
-    });
-  } catch (error) {
-    console.error('Failed to setup window close handler:', error);
-  }
-}

app/src/lib/utils/audio.ts

@@ -17,6 +17,41 @@ export function formatAudioDuration(seconds: number): string {
   return `${mins}:${secs.toString().padStart(2, '0')}`;
 }
 
+/**
+ * Get audio duration from a File.
+ * 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.
+ */
+export async function getAudioDuration(
+  file: File & { recordedDuration?: number },
+): Promise<number> {
+  if (file.recordedDuration !== undefined && Number.isFinite(file.recordedDuration)) {
+    return file.recordedDuration;
+  }
+
+  return new Promise((resolve, reject) => {
+    const audio = new Audio();
+    const url = URL.createObjectURL(file);
+
+    audio.addEventListener('loadedmetadata', () => {
+      URL.revokeObjectURL(url);
+      if (Number.isFinite(audio.duration) && audio.duration > 0) {
+        resolve(audio.duration);
+      } else {
+        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;
+  });
+}
+
 /**
  * Convert any audio blob to WAV format using Web Audio API.
  * This ensures compatibility without requiring ffmpeg on the backend.

app/src/lib/utils/debug.ts

@@ -0,0 +1,19 @@
+const DEBUG = import.meta.env.DEV;
+
+export const debug = {
+  log: (...args: unknown[]) => {
+    if (DEBUG) {
+      console.log(...args);
+    }
+  },
+  error: (...args: unknown[]) => {
+    if (DEBUG) {
+      console.error(...args);
+    }
+  },
+  warn: (...args: unknown[]) => {
+    if (DEBUG) {
+      console.warn(...args);
+    }
+  },
+};

app/src/platform/PlatformContext.tsx

@@ -0,0 +1,25 @@
+import { createContext, useContext, type ReactNode } from 'react';
+import type { Platform } from './types';
+
+const PlatformContext = createContext<Platform | null>(null);
+
+export interface PlatformProviderProps {
+  platform: Platform;
+  children: ReactNode;
+}
+
+export function PlatformProvider({ platform, children }: PlatformProviderProps) {
+  return (
+    <PlatformContext.Provider value={platform}>
+      {children}
+    </PlatformContext.Provider>
+  );
+}
+
+export function usePlatform(): Platform {
+  const platform = useContext(PlatformContext);
+  if (!platform) {
+    throw new Error('usePlatform must be used within PlatformProvider');
+  }
+  return platform;
+}

app/src/platform/types.ts

@@ -0,0 +1,70 @@
+/**
+ * Platform abstraction types
+ * These interfaces define the contract that platform implementations must fulfill
+ */
+
+export interface FileFilter {
+  name: string;
+  extensions: string[];
+}
+
+export interface PlatformFilesystem {
+  saveFile(filename: string, blob: Blob, filters?: FileFilter[]): Promise<void>;
+}
+
+export interface UpdateStatus {
+  checking: boolean;
+  available: boolean;
+  version?: string;
+  downloading: boolean;
+  installing: boolean;
+  readyToInstall: boolean;
+  error?: string;
+  downloadProgress?: number; // 0-100 percentage
+  downloadedBytes?: number;
+  totalBytes?: number;
+}
+
+export interface PlatformUpdater {
+  checkForUpdates(): Promise<void>;
+  downloadAndInstall(): Promise<void>;
+  restartAndInstall(): Promise<void>;
+  getStatus(): UpdateStatus;
+  subscribe(callback: (status: UpdateStatus) => void): () => void;
+}
+
+export interface AudioDevice {
+  id: string;
+  name: string;
+  is_default: boolean;
+}
+
+export interface PlatformAudio {
+  isSystemAudioSupported(): boolean;
+  startSystemAudioCapture(maxDurationSecs: number): Promise<void>;
+  stopSystemAudioCapture(): Promise<Blob>;
+  listOutputDevices(): Promise<AudioDevice[]>;
+  playToDevices(audioData: Uint8Array, deviceIds: string[]): Promise<void>;
+  stopPlayback(): void;
+}
+
+export interface PlatformLifecycle {
+  startServer(remote?: boolean): Promise<string>;
+  stopServer(): Promise<void>;
+  setKeepServerRunning(keep: boolean): Promise<void>;
+  setupWindowCloseHandler(): Promise<void>;
+  onServerReady?: () => void;
+}
+
+export interface PlatformMetadata {
+  getVersion(): Promise<string>;
+  isTauri: boolean;
+}
+
+export interface Platform {
+  filesystem: PlatformFilesystem;
+  updater: PlatformUpdater;
+  audio: PlatformAudio;
+  lifecycle: PlatformLifecycle;
+  metadata: PlatformMetadata;
+}

app/src/router.tsx

@@ -0,0 +1,135 @@
+import { createRootRoute, createRoute, createRouter, Outlet } from '@tanstack/react-router';
+import { AppFrame } from '@/components/AppFrame/AppFrame';
+import { AudioTab } from '@/components/AudioTab/AudioTab';
+import { MainEditor } from '@/components/MainEditor/MainEditor';
+import { ModelsTab } from '@/components/ModelsTab/ModelsTab';
+import { ServerTab } from '@/components/ServerTab/ServerTab';
+import { Sidebar } from '@/components/Sidebar';
+import { StoriesTab } from '@/components/StoriesTab/StoriesTab';
+import { Toaster } from '@/components/ui/toaster';
+import { VoicesTab } from '@/components/VoicesTab/VoicesTab';
+import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
+import { MODEL_DISPLAY_NAMES, useRestoreActiveTasks } from '@/lib/hooks/useRestoreActiveTasks';
+// Simple platform check that works in both web and Tauri
+const isMacOS = () => navigator.platform.toLowerCase().includes('mac');
+
+// Root layout component
+function RootLayout() {
+  // Monitor active downloads/generations and show toasts for them
+  const activeDownloads = useRestoreActiveTasks();
+
+  return (
+    <AppFrame>
+      <div className="flex flex-1 min-h-0 overflow-hidden">
+        <Sidebar isMacOS={isMacOS()} />
+
+        <main className="flex-1 ml-20 overflow-hidden flex flex-col">
+          <div className="container mx-auto px-8 max-w-[1800px] h-full overflow-hidden flex flex-col">
+            <Outlet />
+          </div>
+        </main>
+      </div>
+
+      {/* Show download toasts for any active downloads (from anywhere) */}
+      {activeDownloads.map((download) => {
+        const displayName = MODEL_DISPLAY_NAMES[download.model_name] || download.model_name;
+        return (
+          <DownloadToastRestorer
+            key={download.model_name}
+            modelName={download.model_name}
+            displayName={displayName}
+          />
+        );
+      })}
+
+      <Toaster />
+    </AppFrame>
+  );
+}
+
+/**
+ * Component that restores a download toast for a specific model.
+ */
+function DownloadToastRestorer({
+  modelName,
+  displayName,
+}: {
+  modelName: string;
+  displayName: string;
+}) {
+  // Use the download toast hook to restore the toast
+  useModelDownloadToast({
+    modelName,
+    displayName,
+    enabled: true,
+  });
+
+  return null;
+}
+
+// Root route with layout
+const rootRoute = createRootRoute({
+  component: RootLayout,
+});
+
+// Index route (main/generate)
+const indexRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/',
+  component: MainEditor,
+});
+
+// Stories route
+const storiesRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/stories',
+  component: StoriesTab,
+});
+
+// Voices route
+const voicesRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/voices',
+  component: VoicesTab,
+});
+
+// Audio route
+const audioRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/audio',
+  component: AudioTab,
+});
+
+// Models route
+const modelsRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/models',
+  component: ModelsTab,
+});
+
+// Server route
+const serverRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/server',
+  component: ServerTab,
+});
+
+// Route tree
+const routeTree = rootRoute.addChildren([
+  indexRoute,
+  storiesRoute,
+  voicesRoute,
+  audioRoute,
+  modelsRoute,
+  serverRoute,
+]);
+
+// Create router
+export const router = createRouter({ routeTree });
+
+// Register router for type safety
+declare module '@tanstack/react-router' {
+  interface Register {
+    router: typeof router;
+  }
+}

app/src/stores/playerStore.ts

@@ -11,8 +11,11 @@ interface PlayerState {
   volume: number;
   isLooping: boolean;
   shouldRestart: boolean;
+  shouldAutoPlay: boolean;
+  onFinish: (() => void) | null;
 
   setAudio: (url: string, id: string, profileId: string | null, title?: string) => void;
+  setAudioWithAutoPlay: (url: string, id: string, profileId: string | null, title?: string) => void;
   setIsPlaying: (playing: boolean) => void;
   setCurrentTime: (time: number) => void;
   setDuration: (duration: number) => void;
@@ -20,6 +23,8 @@ interface PlayerState {
   toggleLoop: () => void;
   restartCurrentAudio: () => void;
   clearRestartFlag: () => void;
+  clearAutoPlayFlag: () => void;
+  setOnFinish: (callback: (() => void) | null) => void;
   reset: () => void;
 }
 
@@ -34,6 +39,8 @@ export const usePlayerStore = create<PlayerState>((set) => ({
   volume: 1,
   isLooping: false,
   shouldRestart: false,
+  shouldAutoPlay: false,
+  onFinish: null,
 
   setAudio: (url, id, profileId, title) =>
     set({
@@ -44,6 +51,18 @@ export const usePlayerStore = create<PlayerState>((set) => ({
       currentTime: 0,
       isPlaying: false,
       shouldRestart: false,
+      shouldAutoPlay: false,
+    }),
+  setAudioWithAutoPlay: (url, id, profileId, title) =>
+    set({
+      audioUrl: url,
+      audioId: id,
+      profileId: profileId || null,
+      title: title || null,
+      currentTime: 0,
+      isPlaying: false,
+      shouldRestart: false,
+      shouldAutoPlay: true,
     }),
   setIsPlaying: (playing) => set({ isPlaying: playing }),
   setCurrentTime: (time) => set({ currentTime: time }),
@@ -52,6 +71,8 @@ export const usePlayerStore = create<PlayerState>((set) => ({
   toggleLoop: () => set((state) => ({ isLooping: !state.isLooping })),
   restartCurrentAudio: () => set({ shouldRestart: true }),
   clearRestartFlag: () => set({ shouldRestart: false }),
+  clearAutoPlayFlag: () => set({ shouldAutoPlay: false }),
+  setOnFinish: (callback) => set({ onFinish: callback }),
   reset: () =>
     set({
       audioUrl: null,
@@ -63,5 +84,7 @@ export const usePlayerStore = create<PlayerState>((set) => ({
       duration: 0,
       isLooping: false,
       shouldRestart: false,
+      shouldAutoPlay: false,
+      onFinish: null,
     }),
 }));

app/src/stores/storyStore.ts

@@ -0,0 +1,148 @@
+import { create } from 'zustand';
+import type { StoryItemDetail } from '@/lib/api/types';
+
+interface StoryPlaybackState {
+  // Selection
+  selectedStoryId: string | null;
+  setSelectedStoryId: (id: string | null) => void;
+  selectedClipId: string | null;
+  setSelectedClipId: (id: string | null) => void;
+
+  // Track editor UI state
+  trackEditorHeight: number;
+  setTrackEditorHeight: (height: number) => void;
+
+  // Playback state
+  isPlaying: boolean;
+  currentTimeMs: number;
+  totalDurationMs: number;
+  playbackStoryId: string | null;
+  playbackItems: StoryItemDetail[] | null;
+  // Web Audio API timing (null when not playing)
+  playbackStartContextTime: number | null; // AudioContext.currentTime when playback started
+  playbackStartStoryTime: number | null; // Story time (ms) when playback started
+
+  // Actions
+  play: (storyId: string, items: StoryItemDetail[]) => void;
+  pause: () => void;
+  stop: () => void;
+  seek: (timeMs: number) => void;
+  setPlaybackTiming: (contextTime: number, storyTime: number) => void; // Set timing anchors for Web Audio API
+  setActiveStory: (storyId: string, items: StoryItemDetail[], totalDurationMs: number) => void; // Activate story for seeking without playing
+}
+
+const DEFAULT_TRACK_EDITOR_HEIGHT = 250;
+
+export const useStoryStore = create<StoryPlaybackState>((set, get) => ({
+  // Selection
+  selectedStoryId: null,
+  setSelectedStoryId: (id) => set({ selectedStoryId: id }),
+  selectedClipId: null,
+  setSelectedClipId: (id) => set({ selectedClipId: id }),
+
+  // Track editor UI state
+  trackEditorHeight: DEFAULT_TRACK_EDITOR_HEIGHT,
+  setTrackEditorHeight: (height) => set({ trackEditorHeight: height }),
+
+  // Playback state
+  isPlaying: false,
+  currentTimeMs: 0,
+  totalDurationMs: 0,
+  playbackStoryId: null,
+  playbackItems: null,
+  playbackStartContextTime: null,
+  playbackStartStoryTime: null,
+
+  // Actions
+  play: (storyId, items) => {
+    // Calculate total duration from items
+    const maxEndTimeMs = Math.max(
+      ...items.map((item) => item.start_time_ms + item.duration * 1000),
+      0,
+    );
+
+    // Find the minimum start time (first item)
+    const minStartTimeMs = Math.min(...items.map((item) => item.start_time_ms), 0);
+
+    // If resuming the same story, keep position; otherwise start at first item
+    const currentState = get();
+    const shouldResume = currentState.playbackStoryId === storyId && currentState.currentTimeMs > 0;
+    const startTimeMs = shouldResume ? currentState.currentTimeMs : minStartTimeMs;
+
+    console.log('[StoryStore] Play called:', {
+      storyId,
+      itemCount: items.length,
+      items: items.map((i) => ({
+        id: i.generation_id,
+        start: i.start_time_ms,
+        duration: i.duration,
+      })),
+      maxEndTimeMs,
+      minStartTimeMs,
+      startTimeMs,
+      shouldResume,
+    });
+
+    set({
+      isPlaying: true,
+      playbackStoryId: storyId,
+      playbackItems: items,
+      totalDurationMs: maxEndTimeMs,
+      currentTimeMs: startTimeMs,
+      // Reset timing anchors - will be set fresh by the playback hook
+      playbackStartContextTime: null,
+      playbackStartStoryTime: null,
+    });
+  },
+
+  pause: () => {
+    set({
+      isPlaying: false,
+      // Keep timing anchors so we can resume from same position
+    });
+  },
+
+  stop: () => {
+    set({
+      isPlaying: false,
+      currentTimeMs: 0,
+      playbackStoryId: null,
+      playbackItems: null,
+      totalDurationMs: 0,
+      playbackStartContextTime: null,
+      playbackStartStoryTime: null,
+    });
+  },
+
+  seek: (timeMs) => {
+    const state = get();
+    const clampedTime = Math.max(0, Math.min(timeMs, state.totalDurationMs));
+    set({
+      currentTimeMs: clampedTime,
+      // Reset timing anchors - will be set by hook when playback resumes
+      playbackStartContextTime: null,
+      playbackStartStoryTime: null,
+    });
+  },
+
+  setPlaybackTiming: (contextTime, storyTime) => {
+    set({
+      playbackStartContextTime: contextTime,
+      playbackStartStoryTime: storyTime,
+    });
+  },
+
+  setActiveStory: (storyId, items, totalDurationMs) => {
+    const currentState = get();
+    // Only update if switching to a different story
+    if (currentState.playbackStoryId !== storyId) {
+      set({
+        playbackStoryId: storyId,
+        playbackItems: items,
+        totalDurationMs,
+        currentTimeMs: 0,
+        isPlaying: false,
+      });
+    }
+  },
+}));

app/src/stores/uiStore.ts

@@ -1,5 +1,18 @@
 import { create } from 'zustand';
 
+// Draft state for the create voice profile form
+export interface ProfileFormDraft {
+  name: string;
+  description: string;
+  language: string;
+  referenceText: string;
+  sampleMode: 'upload' | 'record' | 'system';
+  // Note: File objects can't be persisted, so we store metadata
+  sampleFileName?: string;
+  sampleFileType?: string;
+  sampleFileData?: string; // Base64 encoded
+}
+
 interface UIStore {
   // Sidebar
   sidebarOpen: boolean;
@@ -18,6 +31,10 @@ interface UIStore {
   selectedProfileId: string | null;
   setSelectedProfileId: (id: string | null) => void;
 
+  // Profile form draft (for persisting create voice modal state)
+  profileFormDraft: ProfileFormDraft | null;
+  setProfileFormDraft: (draft: ProfileFormDraft | null) => void;
+
   // Theme
   theme: 'light' | 'dark';
   setTheme: (theme: 'light' | 'dark') => void;
@@ -38,6 +55,9 @@ export const useUIStore = create<UIStore>((set) => ({
   selectedProfileId: null,
   setSelectedProfileId: (id) => set({ selectedProfileId: id }),
 
+  profileFormDraft: null,
+  setProfileFormDraft: (draft) => set({ profileFormDraft: draft }),
+
   theme: 'light',
   setTheme: (theme) => {
     set({ theme });

backend/README.md

@@ -19,8 +19,13 @@ Production-quality FastAPI backend for Qwen3-TTS voice cloning.
 backend/
 ├── main.py              # FastAPI app with all routes
 ├── models.py            # Pydantic request/response models
-├── tts.py              # Qwen3-TTS inference
-├── transcribe.py       # Whisper ASR
+├── platform_detect.py   # Platform detection for backend selection
+├── tts.py              # TTS backend abstraction (delegates to MLX or PyTorch)
+├── transcribe.py       # STT backend abstraction (delegates to MLX or PyTorch)
+├── backends/           # Backend implementations
+│   ├── __init__.py     # Backend factory and protocols
+│   ├── mlx_backend.py  # MLX backend (Apple Silicon)
+│   └── pytorch_backend.py  # PyTorch backend (Windows/Linux/Intel)
 ├── profiles.py         # Voice profile CRUD
 ├── history.py          # Generation history
 ├── studio.py           # Audio editing (TODO)
@@ -31,6 +36,15 @@ backend/
     └── validation.py   # Input validation
 ```
 
+### Backend Selection
+
+Voicebox automatically selects the best backend based on platform:
+
+- **Apple Silicon (M1/M2/M3)**: Uses MLX backend with native Metal acceleration (4-5x faster)
+- **Windows/Linux/Intel Mac**: Uses PyTorch backend (CUDA GPU if available, CPU fallback)
+
+The backend is detected at runtime via `platform_detect.py`. Both backends implement the same interface, so the API remains consistent across platforms.
+
 ## API Endpoints
 
 ### Health & Info
@@ -47,12 +61,20 @@ Health check with model status.
   "status": "healthy",
   "model_loaded": true,
   "gpu_available": true,
-  "vram_used_mb": 1024.5
+  "gpu_type": "Metal (Apple Silicon via MLX)",
+  "backend_type": "mlx",
+  "vram_used_mb": null
 }
 ```
 
+**Backend Types:**
+- `"mlx"` - MLX backend (Apple Silicon with Metal acceleration)
+- `"pytorch"` - PyTorch backend (Windows/Linux/Intel Mac)
+
 ### Voice Profiles
 
+**Note:** The database is automatically initialized when the server starts. No manual setup required.
+
 #### `POST /profiles`
 Create a new voice profile.
 
@@ -266,13 +288,12 @@ data/
 pip install -r requirements.txt
 ```
 
-### 2. Initialize Database
-
+**Note:** On Apple Silicon, also install MLX dependencies for faster inference:
 ```bash
-python -c "from database import init_db; init_db()"
+pip install -r requirements-mlx.txt
 ```
 
-### 3. Download Models (Automatic)
+### 2. Download Models (Automatic)
 
 The Qwen3-TTS models are automatically downloaded from HuggingFace Hub on first use, similar to how Whisper models work.
 

backend/__init__.py

@@ -1 +1,3 @@
 # Backend package
+
+__version__ = "0.1.12"

backend/backends/__init__.py

@@ -0,0 +1,166 @@
+"""
+Backend abstraction layer for TTS and STT.
+
+Provides a unified interface for MLX and PyTorch backends.
+"""
+
+from typing import Protocol, Optional, Tuple, List
+from typing_extensions import runtime_checkable
+import numpy as np
+
+from ..platform_detect import get_backend_type
+
+
+@runtime_checkable
+class TTSBackend(Protocol):
+    """Protocol for TTS backend implementations."""
+    
+    async def load_model(self, model_size: str) -> None:
+        """Load TTS model."""
+        ...
+    
+    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.
+        
+        Returns:
+            Tuple of (voice_prompt_dict, was_cached)
+        """
+        ...
+    
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple voice prompts.
+        
+        Returns:
+            Tuple of (combined_audio_array, 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.
+        
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        ...
+    
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        ...
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        ...
+    
+    def _get_model_path(self, model_size: str) -> str:
+        """
+        Get model path for a given size.
+        
+        Returns:
+            Model path or HuggingFace Hub ID
+        """
+        ...
+
+
+@runtime_checkable
+class STTBackend(Protocol):
+    """Protocol for STT (Speech-to-Text) backend implementations."""
+    
+    async def load_model(self, model_size: str) -> None:
+        """Load STT model."""
+        ...
+    
+    async def transcribe(
+        self,
+        audio_path: str,
+        language: Optional[str] = None,
+    ) -> str:
+        """
+        Transcribe audio to text.
+        
+        Returns:
+            Transcribed text
+        """
+        ...
+    
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        ...
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        ...
+
+
+# Global backend instances
+_tts_backend: Optional[TTSBackend] = None
+_stt_backend: Optional[STTBackend] = None
+
+
+def get_tts_backend() -> TTSBackend:
+    """
+    Get or create TTS backend instance based on platform.
+    
+    Returns:
+        TTS backend instance (MLX or PyTorch)
+    """
+    global _tts_backend
+    
+    if _tts_backend is None:
+        backend_type = get_backend_type()
+        
+        if backend_type == "mlx":
+            from .mlx_backend import MLXTTSBackend
+            _tts_backend = MLXTTSBackend()
+        else:
+            from .pytorch_backend import PyTorchTTSBackend
+            _tts_backend = PyTorchTTSBackend()
+    
+    return _tts_backend
+
+
+def get_stt_backend() -> STTBackend:
+    """
+    Get or create STT backend instance based on platform.
+    
+    Returns:
+        STT backend instance (MLX or PyTorch)
+    """
+    global _stt_backend
+    
+    if _stt_backend is None:
+        backend_type = get_backend_type()
+        
+        if backend_type == "mlx":
+            from .mlx_backend import MLXSTTBackend
+            _stt_backend = MLXSTTBackend()
+        else:
+            from .pytorch_backend import PyTorchSTTBackend
+            _stt_backend = PyTorchSTTBackend()
+    
+    return _stt_backend
+
+
+def reset_backends():
+    """Reset backend instances (useful for testing)."""
+    global _tts_backend, _stt_backend
+    _tts_backend = None
+    _stt_backend = None

backend/backends/mlx_backend.py

@@ -0,0 +1,573 @@
+"""
+MLX backend implementation for TTS and STT using mlx-audio.
+"""
+
+from typing import Optional, List, Tuple
+import asyncio
+import numpy as np
+from pathlib import Path
+
+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
+from ..utils.progress import get_progress_manager
+from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+from ..utils.tasks import get_task_manager
+
+
+class MLXTTSBackend:
+    """MLX-based TTS backend using mlx-audio."""
+    
+    def __init__(self, model_size: str = "1.7B"):
+        self.model = None
+        self.model_size = model_size
+        self._current_model_size = None
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        return self.model is not None
+    
+    def _get_model_path(self, model_size: str) -> str:
+        """
+        Get the MLX model path.
+        
+        Args:
+            model_size: Model size (1.7B or 0.6B)
+            
+        Returns:
+            HuggingFace Hub model ID for MLX
+        """
+        # MLX model mapping
+        mlx_model_map = {
+            "1.7B": "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16",
+            # 0.6B not yet converted to MLX format
+            "0.6B": "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16",  # Fallback to 1.7B
+        }
+        
+        if model_size not in mlx_model_map:
+            raise ValueError(f"Unknown model size: {model_size}")
+        
+        hf_model_id = mlx_model_map[model_size]
+        print(f"Will download MLX model from HuggingFace Hub: {hf_model_id}")
+        
+        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.
+        
+        Args:
+            model_size: Model size to load (1.7B or 0.6B)
+        """
+        if model_size is None:
+            model_size = self.model_size
+            
+        # If already loaded with correct size, return
+        if self.model is not None and self._current_model_size == model_size:
+            return
+        
+        # Unload existing model if different size requested
+        if self.model is not None and self._current_model_size != model_size:
+            self.unload_model()
+        
+        # Run blocking load in thread pool
+        await asyncio.to_thread(self._load_model_sync, model_size)
+    
+    # Alias for compatibility
+    load_model = load_model_async
+    
+    def _load_model_sync(self, model_size: str):
+        """Synchronous model loading."""
+        try:
+            # Get model path BEFORE importing mlx_audio
+            model_path = self._get_model_path(model_size)
+            
+            # Set up progress tracking
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+            
+            # Check if model is already cached
+            is_cached = self._is_model_cached(model_size)
+            
+            # Set up progress callback
+            # If cached: filter out non-download progress
+            # If not cached: report all progress (we're actually downloading)
+            progress_callback = create_hf_progress_callback(model_name, progress_manager)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+            
+            print(f"Loading MLX TTS model {model_size}...")
+            
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(model_name)
+                
+                # Initialize progress state so SSE endpoint has initial data to send
+                # This provides immediate feedback while HuggingFace fetches metadata
+                progress_manager.update_progress(
+                    model_name=model_name,
+                    current=0,
+                    total=0,  # Will be updated once actual total is known
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+            
+            # IMPORTANT: Patch tqdm BEFORE importing mlx_audio
+            # Otherwise mlx_audio caches reference to original tqdm
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+            
+            # Import mlx_audio AFTER patching tqdm
+            from mlx_audio.tts import load
+            
+            # Load MLX model (downloads automatically)
+            try:
+                self.model = load(model_path)
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+            
+            self._current_model_size = model_size
+            self.model_size = model_size
+            
+            print(f"MLX TTS model {model_size} loaded successfully")
+            
+        except ImportError as e:
+            print(f"Error: mlx_audio package not found. Install with: pip install mlx-audio")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+            progress_manager.mark_error(model_name, str(e))
+            task_manager.error_download(model_name, str(e))
+            raise
+        except Exception as e:
+            print(f"Error loading MLX TTS model: {e}")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+            progress_manager.mark_error(model_name, str(e))
+            task_manager.error_download(model_name, str(e))
+            raise
+    
+    def unload_model(self):
+        """Unload the model to free memory."""
+        if self.model is not None:
+            del self.model
+            self.model = None
+            self._current_model_size = None
+            print("MLX TTS model 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.
+        
+        MLX backend stores voice prompt as a dict with audio path and text.
+        The actual voice prompt processing happens during generation.
+        
+        Args:
+            audio_path: Path to reference audio file
+            reference_text: Transcript of reference audio
+            use_cache: Whether to use cached prompt if available
+            
+        Returns:
+            Tuple of (voice_prompt_dict, was_cached)
+        """
+        await self.load_model_async(None)
+        
+        # Check cache if enabled
+        if use_cache:
+            cache_key = get_cache_key(audio_path, reference_text)
+            cached_prompt = get_cached_voice_prompt(cache_key)
+            if cached_prompt is not None:
+                # Return cached prompt (should be dict format)
+                if isinstance(cached_prompt, dict):
+                    # Validate that the cached audio file still exists
+                    cached_audio_path = cached_prompt.get("ref_audio") or cached_prompt.get("ref_audio_path")
+                    if cached_audio_path and Path(cached_audio_path).exists():
+                        return cached_prompt, True
+                    else:
+                        # Cached file no longer exists, invalidate cache
+                        print(f"Cached audio file not found: {cached_audio_path}, regenerating prompt")
+        
+        # MLX voice prompt format - store audio path and text
+        # The model will process this during generation
+        voice_prompt_items = {
+            "ref_audio": str(audio_path),
+            "ref_text": reference_text,
+        }
+        
+        # Cache if enabled
+        if use_cache:
+            cache_key = get_cache_key(audio_path, reference_text)
+            cache_voice_prompt(cache_key, voice_prompt_items)
+        
+        return voice_prompt_items, False
+    
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple reference samples for better quality.
+        
+        Args:
+            audio_paths: List of audio file paths
+            reference_texts: List of reference texts
+            
+        Returns:
+            Tuple of (combined_audio, combined_text)
+        """
+        combined_audio = []
+        
+        for audio_path in audio_paths:
+            audio, sr = load_audio(audio_path)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+        
+        # Concatenate audio
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        
+        # Combine texts
+        combined_text = " ".join(reference_texts)
+        
+        return mixed, combined_text
+    
+    async def 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 voice prompt.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Voice prompt dictionary with ref_audio and ref_text
+            language: Language code (en or zh) - may not be fully supported by MLX
+            seed: Random seed for reproducibility
+            instruct: Natural language instruction (may not be supported by MLX)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model_async(None)
+
+        print(f"Generating audio for text: {text}")
+
+        def _generate_sync():
+            """Run synchronous generation in thread pool."""
+            # MLX generate() returns a generator yielding GenerationResult objects
+            audio_chunks = []
+            sample_rate = 24000
+            
+            # Set seed if provided (MLX uses numpy random)
+            if seed is not None:
+                import mlx.core as mx
+                np.random.seed(seed)
+                mx.random.seed(seed)
+            
+            # Extract voice prompt info
+            ref_audio = voice_prompt.get("ref_audio") or voice_prompt.get("ref_audio_path")
+            ref_text = voice_prompt.get("ref_text", "")
+            
+            # Validate that the audio file exists
+            if ref_audio and not Path(ref_audio).exists():
+                print(f"Warning: Audio file not found: {ref_audio}")
+                print("This may be due to a cached voice prompt referencing a deleted temp file.")
+                print("Regenerating without voice prompt.")
+                ref_audio = None
+            
+            # Check if model supports voice cloning via generate method
+            # MLX API may support ref_audio parameter directly
+            try:
+                # Try with voice cloning parameters if supported
+                if ref_audio:
+                    # Check if generate accepts ref_audio parameter
+                    import inspect
+                    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):
+                            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):
+                            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):
+                        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):
+                    audio_chunks.append(np.array(result.audio))
+                    sample_rate = result.sample_rate
+            
+            # Concatenate all chunks
+            if audio_chunks:
+                audio = np.concatenate([np.asarray(chunk, dtype=np.float32) for chunk in audio_chunks])
+            else:
+                # Fallback: empty audio
+                audio = np.array([], dtype=np.float32)
+            
+            return audio, sample_rate
+
+        # Run blocking inference in thread pool
+        audio, sample_rate = await asyncio.to_thread(_generate_sync)
+
+        return audio, sample_rate
+
+
+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
+    
+    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
+            model_name = f"openai/whisper-{model_size}"
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_name.replace("/", "--"))
+            
+            if not repo_cache.exists():
+                return False
+            
+            # Check for .incomplete files - if any exist, download is still in progress
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                print(f"[_is_model_cached] Found .incomplete files for whisper-{model_size}, treating as not cached")
+                return False
+            
+            # Check that actual model weight files exist in snapshots
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = (
+                    any(snapshots_dir.rglob("*.safetensors")) or
+                    any(snapshots_dir.rglob("*.bin")) or
+                    any(snapshots_dir.rglob("*.npz"))
+                )
+                if not has_weights:
+                    print(f"[_is_model_cached] No model weights found for whisper-{model_size}, treating as not cached")
+                    return False
+            
+            return True
+        except Exception as e:
+            print(f"[_is_model_cached] Error checking cache for whisper-{model_size}: {e}")
+            return False
+    
+    async def load_model_async(self, model_size: Optional[str] = None):
+        """
+        Lazy load the MLX Whisper model.
+        
+        Args:
+            model_size: Model size (tiny, base, small, medium, large)
+        """
+        if model_size is None:
+            model_size = self.model_size
+        
+        if self.model is not None and self.model_size == model_size:
+            return
+        
+        # Run blocking load in thread pool
+        await asyncio.to_thread(self._load_model_sync, model_size)
+    
+    # Alias for compatibility
+    load_model = load_model_async
+    
+    def _load_model_sync(self, model_size: str):
+        """Synchronous model loading."""
+        try:
+            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, filter_non_downloads=is_cached)
+
+            # Patch tqdm BEFORE importing mlx_audio
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+
+            # Import mlx_audio
+            from mlx_audio.stt import load
+
+            # MLX Whisper uses the standard OpenAI models
+            model_name = f"openai/whisper-{model_size}"
+
+            print(f"Loading MLX Whisper model {model_size}...")
+
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(progress_model_name)
+                
+                # Initialize progress state so SSE endpoint has initial data to send
+                progress_manager.update_progress(
+                    model_name=progress_model_name,
+                    current=0,
+                    total=0,
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+
+            # Load the model (tqdm is patched, but filters out non-download progress)
+            try:
+                self.model = load(model_name)
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(progress_model_name)
+                task_manager.complete_download(progress_model_name)
+            
+            self.model_size = model_size
+            
+            print(f"MLX Whisper model {model_size} loaded successfully")
+            
+        except ImportError as e:
+            print(f"Error: mlx_audio package not found. Install with: pip install mlx-audio")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            progress_model_name = f"whisper-{model_size}"
+            progress_manager.mark_error(progress_model_name, str(e))
+            task_manager.error_download(progress_model_name, str(e))
+            raise
+        except Exception as e:
+            print(f"Error loading MLX Whisper model: {e}")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            progress_model_name = f"whisper-{model_size}"
+            progress_manager.mark_error(progress_model_name, str(e))
+            task_manager.error_download(progress_model_name, str(e))
+            raise
+    
+    def unload_model(self):
+        """Unload the model to free memory."""
+        if self.model is not None:
+            del self.model
+            self.model = None
+            print("MLX Whisper model unloaded")
+    
+    async def transcribe(
+        self,
+        audio_path: str,
+        language: Optional[str] = None,
+    ) -> str:
+        """
+        Transcribe audio to text.
+
+        Args:
+            audio_path: Path to audio file
+            language: Optional language hint (en or zh)
+
+        Returns:
+            Transcribed text
+        """
+        await self.load_model_async(None)
+
+        def _transcribe_sync():
+            """Run synchronous transcription in thread pool."""
+            # MLX Whisper transcription using generate method
+            # The generate method accepts audio path directly
+            decode_options = {}
+            if language:
+                decode_options["language"] = language
+
+            result = self.model.generate(str(audio_path), **decode_options)
+
+            # Extract text from result
+            if isinstance(result, str):
+                return result.strip()
+            elif isinstance(result, dict):
+                return result.get("text", "").strip()
+            elif hasattr(result, "text"):
+                return result.text.strip()
+            else:
+                return str(result).strip()
+
+        # Run blocking transcription in thread pool
+        return await asyncio.to_thread(_transcribe_sync)

backend/backends/pytorch_backend.py

@@ -0,0 +1,575 @@
+"""
+PyTorch backend implementation for TTS and STT.
+"""
+
+from typing import Optional, List, Tuple
+import asyncio
+import torch
+import numpy as np
+from pathlib import Path
+
+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
+from ..utils.progress import get_progress_manager
+from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+from ..utils.tasks import get_task_manager
+
+
+class PyTorchTTSBackend:
+    """PyTorch-based TTS backend using Qwen3-TTS."""
+    
+    def __init__(self, model_size: str = "1.7B"):
+        self.model = None
+        self.model_size = model_size
+        self.device = self._get_device()
+        self._current_model_size = None
+    
+    def _get_device(self) -> str:
+        """Get the best available device."""
+        if torch.cuda.is_available():
+            return "cuda"
+        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+            # MPS can have issues, use CPU for stability
+            return "cpu"
+        return "cpu"
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        return self.model is not None
+    
+    def _get_model_path(self, model_size: str) -> str:
+        """
+        Get the HuggingFace Hub model ID.
+        
+        Args:
+            model_size: Model size (1.7B or 0.6B)
+            
+        Returns:
+            HuggingFace Hub model ID
+        """
+        hf_model_map = {
+            "1.7B": "Qwen/Qwen3-TTS-12Hz-1.7B-Base",
+            "0.6B": "Qwen/Qwen3-TTS-12Hz-0.6B-Base",
+        }
+        
+        if model_size not in hf_model_map:
+            raise ValueError(f"Unknown model size: {model_size}")
+        
+        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.
+        
+        Args:
+            model_size: Model size to load (1.7B or 0.6B)
+        """
+        if model_size is None:
+            model_size = self.model_size
+            
+        # If already loaded with correct size, return
+        if self.model is not None and self._current_model_size == model_size:
+            return
+        
+        # Unload existing model if different size requested
+        if self.model is not None and self._current_model_size != model_size:
+            self.unload_model()
+        
+        # Run blocking load in thread pool
+        await asyncio.to_thread(self._load_model_sync, model_size)
+    
+    # Alias for compatibility
+    load_model = load_model_async
+    
+    def _load_model_sync(self, model_size: str):
+        """Synchronous model loading."""
+        try:
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+
+            # Check if model is already cached
+            is_cached = self._is_model_cached(model_size)
+
+            # Set up progress callback and tracker
+            # If cached: filter out non-download progress (like "Segment 1/1" during generation)
+            # If not cached: report all progress (we're actually downloading)
+            progress_callback = create_hf_progress_callback(model_name, progress_manager)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+
+            # Patch tqdm BEFORE importing qwen_tts
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+
+            # Import qwen_tts
+            from qwen_tts import Qwen3TTSModel
+
+            # Get model path (local or HuggingFace Hub ID)
+            model_path = self._get_model_path(model_size)
+
+            print(f"Loading TTS model {model_size} on {self.device}...")
+
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(model_name)
+
+                # Initialize progress state so SSE endpoint has initial data to send
+                progress_manager.update_progress(
+                    model_name=model_name,
+                    current=0,
+                    total=0,  # Will be updated once actual total is known
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+
+            # Load the model (tqdm is patched, but filters out non-download progress)
+            try:
+                self.model = Qwen3TTSModel.from_pretrained(
+                    model_path,
+                    device_map=self.device,
+                    torch_dtype=torch.float32 if self.device == "cpu" else torch.bfloat16,
+                )
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # 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
+            
+            print(f"TTS model {model_size} loaded successfully")
+            
+        except ImportError as e:
+            print(f"Error: qwen_tts package not found. Install with: pip install git+https://github.com/QwenLM/Qwen3-TTS.git")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+            progress_manager.mark_error(model_name, str(e))
+            task_manager.error_download(model_name, str(e))
+            raise
+        except Exception as e:
+            print(f"Error loading TTS model: {e}")
+            print(f"Tip: The model will be automatically downloaded from HuggingFace Hub on first use.")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+            progress_manager.mark_error(model_name, str(e))
+            task_manager.error_download(model_name, str(e))
+            raise
+    
+    def unload_model(self):
+        """Unload the model to free memory."""
+        if self.model is not None:
+            del self.model
+            self.model = None
+            self._current_model_size = None
+            
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+            
+            print("TTS model 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.
+        
+        Args:
+            audio_path: Path to reference audio file
+            reference_text: Transcript of reference audio
+            use_cache: Whether to use cached prompt if available
+            
+        Returns:
+            Tuple of (voice_prompt_dict, was_cached)
+        """
+        await self.load_model_async(None)
+        
+        # Check cache if enabled
+        if use_cache:
+            cache_key = get_cache_key(audio_path, reference_text)
+            cached_prompt = get_cached_voice_prompt(cache_key)
+            if cached_prompt is not None:
+                # Cache stores as torch.Tensor but actual prompt is dict
+                # Convert if needed
+                if isinstance(cached_prompt, dict):
+                    # For PyTorch backend, the dict should contain tensors, not file paths
+                    # So we can safely return it
+                    return cached_prompt, True
+                elif isinstance(cached_prompt, torch.Tensor):
+                    # Legacy cache format - convert to dict
+                    # This shouldn't happen in practice, but handle it
+                    return {"prompt": cached_prompt}, True
+        
+        def _create_prompt_sync():
+            """Run synchronous voice prompt creation in thread pool."""
+            return self.model.create_voice_clone_prompt(
+                ref_audio=str(audio_path),
+                ref_text=reference_text,
+                x_vector_only_mode=False,
+            )
+        
+        # Run blocking operation in thread pool
+        voice_prompt_items = await asyncio.to_thread(_create_prompt_sync)
+        
+        # Cache if enabled
+        if use_cache:
+            cache_key = get_cache_key(audio_path, reference_text)
+            cache_voice_prompt(cache_key, voice_prompt_items)
+        
+        return voice_prompt_items, False
+    
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple reference samples for better quality.
+        
+        Args:
+            audio_paths: List of audio file paths
+            reference_texts: List of reference texts
+            
+        Returns:
+            Tuple of (combined_audio, combined_text)
+        """
+        combined_audio = []
+        
+        for audio_path in audio_paths:
+            audio, sr = load_audio(audio_path)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+        
+        # Concatenate audio
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        
+        # Combine texts
+        combined_text = " ".join(reference_texts)
+        
+        return mixed, combined_text
+    
+    async def 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 voice prompt.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Voice prompt dictionary from create_voice_prompt
+            language: Language code (en or zh)
+            seed: Random seed for reproducibility
+            instruct: Natural language instruction for speech delivery control
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        # Load model
+        await self.load_model_async(None)
+
+        def _generate_sync():
+            """Run synchronous generation in thread pool."""
+            # Set seed if provided
+            if seed is not None:
+                torch.manual_seed(seed)
+                if torch.cuda.is_available():
+                    torch.cuda.manual_seed(seed)
+
+            # Generate audio - this is the blocking operation
+            wavs, sample_rate = self.model.generate_voice_clone(
+                text=text,
+                voice_clone_prompt=voice_prompt,
+                instruct=instruct,
+            )
+            return wavs[0], sample_rate
+
+        # Run blocking inference in thread pool to avoid blocking event loop
+        audio, sample_rate = await asyncio.to_thread(_generate_sync)
+
+        return audio, sample_rate
+
+
+class PyTorchSTTBackend:
+    """PyTorch-based STT backend using Whisper."""
+    
+    def __init__(self, model_size: str = "base"):
+        self.model = None
+        self.processor = None
+        self.model_size = model_size
+        self.device = self._get_device()
+    
+    def _get_device(self) -> str:
+        """Get the best available device."""
+        if torch.cuda.is_available():
+            return "cuda"
+        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+            # MPS support for Whisper
+            return "cpu"  # Use CPU 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
+            model_name = f"openai/whisper-{model_size}"
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_name.replace("/", "--"))
+            
+            if not repo_cache.exists():
+                return False
+            
+            # Check for .incomplete files - if any exist, download is still in progress
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                print(f"[_is_model_cached] Found .incomplete files for whisper-{model_size}, treating as not cached")
+                return False
+            
+            # Check that actual model weight files exist in snapshots
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = (
+                    any(snapshots_dir.rglob("*.safetensors")) or
+                    any(snapshots_dir.rglob("*.bin"))
+                )
+                if not has_weights:
+                    print(f"[_is_model_cached] No model weights found for whisper-{model_size}, treating as not cached")
+                    return False
+            
+            return True
+        except Exception as e:
+            print(f"[_is_model_cached] Error checking cache for whisper-{model_size}: {e}")
+            return False
+    
+    async def load_model_async(self, model_size: Optional[str] = None):
+        """
+        Lazy load the Whisper model.
+
+        Args:
+            model_size: Model size (tiny, base, small, medium, large)
+        """
+        print(f"[DEBUG] load_model_async called with size: {model_size}")
+        if model_size is None:
+            model_size = self.model_size
+
+        print(f"[DEBUG] Model already loaded? {self.model is not None}, current size: {self.model_size}, requested: {model_size}")
+        if self.model is not None and self.model_size == model_size:
+            print(f"[DEBUG] Early return - model already loaded")
+            return
+
+        print(f"[DEBUG] Calling asyncio.to_thread for _load_model_sync")
+        # Run blocking load in thread pool
+        await asyncio.to_thread(self._load_model_sync, model_size)
+        print(f"[DEBUG] asyncio.to_thread completed")
+    
+    # Alias for compatibility
+    load_model = load_model_async
+    
+    def _load_model_sync(self, model_size: str):
+        """Synchronous model loading."""
+        print(f"[DEBUG] _load_model_sync called for Whisper {model_size}")
+        try:
+            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, filter_non_downloads=is_cached)
+
+            # Patch tqdm BEFORE importing transformers
+            print("[DEBUG] Starting tqdm patch BEFORE transformers import")
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+            print("[DEBUG] tqdm patched, now importing transformers")
+
+            # Import transformers
+            from transformers import WhisperProcessor, WhisperForConditionalGeneration
+
+            model_name = f"openai/whisper-{model_size}"
+            print(f"[DEBUG] Model name: {model_name}")
+
+            print(f"Loading Whisper model {model_size} on {self.device}...")
+
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(progress_model_name)
+
+                # Initialize progress state so SSE endpoint has initial data to send
+                progress_manager.update_progress(
+                    model_name=progress_model_name,
+                    current=0,
+                    total=0,  # Will be updated once actual total is known
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+
+            # Load models (tqdm is patched, but filters out non-download progress)
+            try:
+                self.processor = WhisperProcessor.from_pretrained(model_name)
+                self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(progress_model_name)
+                task_manager.complete_download(progress_model_name)
+            
+            self.model.to(self.device)
+            self.model_size = model_size
+            
+            print(f"Whisper model {model_size} loaded successfully")
+            
+        except Exception as e:
+            print(f"Error loading Whisper model: {e}")
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            progress_model_name = f"whisper-{model_size}"
+            progress_manager.mark_error(progress_model_name, str(e))
+            task_manager.error_download(progress_model_name, str(e))
+            raise
+    
+    def unload_model(self):
+        """Unload the model to free memory."""
+        if self.model is not None:
+            del self.model
+            del self.processor
+            self.model = None
+            self.processor = None
+            
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+            
+            print("Whisper model unloaded")
+    
+    async def transcribe(
+        self,
+        audio_path: str,
+        language: Optional[str] = None,
+    ) -> str:
+        """
+        Transcribe audio to text.
+        
+        Args:
+            audio_path: Path to audio file
+            language: Optional language hint (en or zh)
+            
+        Returns:
+            Transcribed text
+        """
+        await self.load_model_async(None)
+        
+        def _transcribe_sync():
+            """Run synchronous transcription in thread pool."""
+            # Load audio
+            audio, sr = load_audio(audio_path, sample_rate=16000)
+            
+            # Process audio
+            inputs = self.processor(
+                audio,
+                sampling_rate=16000,
+                return_tensors="pt",
+            )
+            inputs = inputs.to(self.device)
+            
+            # Set language if provided
+            forced_decoder_ids = None
+            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 transcription
+            with torch.no_grad():
+                predicted_ids = self.model.generate(
+                    inputs["input_features"],
+                    forced_decoder_ids=forced_decoder_ids,
+                )
+            
+            # Decode
+            transcription = self.processor.batch_decode(
+                predicted_ids,
+                skip_special_tokens=True,
+            )[0]
+            
+            return transcription.strip()
+        
+        # Run blocking transcription in thread pool
+        return await asyncio.to_thread(_transcribe_sync)

backend/build_binary.py

@@ -4,16 +4,19 @@ PyInstaller build script for creating standalone Python server binary.
 
 import PyInstaller.__main__
 import os
+import platform
 from pathlib import Path
 
 
+def is_apple_silicon():
+    """Check if running on Apple Silicon."""
+    return platform.system() == "Darwin" and platform.machine() == "arm64"
+
+
 def build_server():
     """Build Python server as standalone binary."""
     backend_dir = Path(__file__).parent
 
-    # Check for local editable qwen_tts install
-    local_qwen_path = Path.home() / 'Projects' / 'voice' / 'Qwen3-TTS'
-
     # PyInstaller arguments
     args = [
         'server.py',  # Use server.py as entry point instead of main.py
@@ -21,12 +24,13 @@ def build_server():
         '--name', 'voicebox-server',
     ]
 
-    # Add local qwen_tts path if it exists (for editable installs)
-    if local_qwen_path.exists():
-        args.extend(['--paths', str(local_qwen_path)])
-        print(f"Using local qwen_tts source from: {local_qwen_path}")
+    # Add local qwen_tts path if specified (for editable installs)
+    qwen_tts_path = os.getenv('QWEN_TTS_PATH')
+    if qwen_tts_path and Path(qwen_tts_path).exists():
+        args.extend(['--paths', str(qwen_tts_path)])
+        print(f"Using local qwen_tts source from: {qwen_tts_path}")
 
-    # Add hidden imports
+    # Add common hidden imports
     args.extend([
         '--hidden-import', 'backend',
         '--hidden-import', 'backend.main',
@@ -37,6 +41,9 @@ def build_server():
         '--hidden-import', 'backend.history',
         '--hidden-import', 'backend.tts',
         '--hidden-import', 'backend.transcribe',
+        '--hidden-import', 'backend.platform_detect',
+        '--hidden-import', 'backend.backends',
+        '--hidden-import', 'backend.backends.pytorch_backend',
         '--hidden-import', 'backend.utils.audio',
         '--hidden-import', 'backend.utils.cache',
         '--hidden-import', 'backend.utils.progress',
@@ -61,6 +68,29 @@ def build_server():
         # Fix for pkg_resources and jaraco namespace packages
         '--hidden-import', 'pkg_resources.extern',
         '--collect-submodules', 'jaraco',
+    ])
+
+    # Add MLX-specific imports if building on Apple Silicon
+    if is_apple_silicon():
+        print("Building for Apple Silicon - including MLX dependencies")
+        args.extend([
+            '--hidden-import', 'backend.backends.mlx_backend',
+            '--hidden-import', 'mlx',
+            '--hidden-import', 'mlx.core',
+            '--hidden-import', 'mlx.nn',
+            '--hidden-import', 'mlx_audio',
+            '--hidden-import', 'mlx_audio.tts',
+            '--hidden-import', 'mlx_audio.stt',
+            '--collect-submodules', 'mlx',
+            '--collect-submodules', 'mlx_audio',
+            # Collect MLX data files including Metal shader libraries (.metallib)
+            '--collect-data', 'mlx',
+            '--collect-data', 'mlx_audio',
+        ])
+    else:
+        print("Building for non-Apple Silicon platform - PyTorch only")
+
+    args.extend([
         '--noconfirm',
         '--clean',
     ])

backend/database.py

@@ -17,11 +17,12 @@ Base = declarative_base()
 class VoiceProfile(Base):
     """Voice profile database model."""
     __tablename__ = "profiles"
-    
+
     id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
     name = Column(String, unique=True, nullable=False)
     description = Column(Text)
     language = Column(String, default="en")
+    avatar_path = Column(String, nullable=True)
     created_at = Column(DateTime, default=datetime.utcnow)
     updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
 
@@ -51,6 +52,31 @@ class Generation(Base):
     created_at = Column(DateTime, default=datetime.utcnow)
 
 
+class Story(Base):
+    """Story database model."""
+    __tablename__ = "stories"
+    
+    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
+    name = Column(String, nullable=False)
+    description = Column(Text)
+    created_at = Column(DateTime, default=datetime.utcnow)
+    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
+
+
+class StoryItem(Base):
+    """Story item database model (links generations to stories)."""
+    __tablename__ = "story_items"
+    
+    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
+    story_id = Column(String, ForeignKey("stories.id"), nullable=False)
+    generation_id = Column(String, ForeignKey("generations.id"), nullable=False)
+    start_time_ms = Column(Integer, nullable=False, default=0)  # Milliseconds from story start
+    track = Column(Integer, nullable=False, default=0)  # Track number (0 = main track)
+    trim_start_ms = Column(Integer, nullable=False, default=0)  # Milliseconds trimmed from start
+    trim_end_ms = Column(Integer, nullable=False, default=0)  # Milliseconds trimmed from end
+    created_at = Column(DateTime, default=datetime.utcnow)
+
+
 class Project(Base):
     """Audio studio project database model."""
     __tablename__ = "projects"
@@ -108,6 +134,10 @@ def init_db():
     )
 
     SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+    
+    # Run migrations before creating tables
+    _run_migrations(engine)
+    
     Base.metadata.create_all(bind=engine)
     
     # Create default channel if it doesn't exist
@@ -136,6 +166,129 @@ def init_db():
         db.close()
 
 
+def _run_migrations(engine):
+    """Run database migrations."""
+    from sqlalchemy import inspect, text
+    
+    inspector = inspect(engine)
+    
+    # Check if story_items table exists
+    if 'story_items' not in inspector.get_table_names():
+        return  # Table doesn't exist yet, will be created fresh
+    
+    # Get columns in story_items table
+    columns = {col['name'] for col in inspector.get_columns('story_items')}
+    
+    # Migration: Remove position column and ensure start_time_ms exists
+    # SQLite doesn't support DROP COLUMN easily, so we recreate the table
+    if 'position' in columns:
+        print("Migrating story_items: removing position column, using start_time_ms")
+        
+        with engine.connect() as conn:
+            # Check if start_time_ms already exists
+            has_start_time = 'start_time_ms' in columns
+            
+            if not has_start_time:
+                # First, add the new column temporarily
+                conn.execute(text("ALTER TABLE story_items ADD COLUMN start_time_ms INTEGER DEFAULT 0"))
+                
+                # Calculate timecodes from position ordering
+                result = conn.execute(text("""
+                    SELECT si.id, si.story_id, si.position, g.duration
+                    FROM story_items si
+                    JOIN generations g ON si.generation_id = g.id
+                    ORDER BY si.story_id, si.position
+                """))
+                
+                rows = result.fetchall()
+                
+                current_story_id = None
+                current_time_ms = 0
+                
+                for row in rows:
+                    item_id, story_id, position, duration = row
+                    
+                    if story_id != current_story_id:
+                        current_story_id = story_id
+                        current_time_ms = 0
+                    
+                    conn.execute(
+                        text("UPDATE story_items SET start_time_ms = :time WHERE id = :id"),
+                        {"time": current_time_ms, "id": item_id}
+                    )
+                    
+                    current_time_ms += int(duration * 1000) + 200
+                
+                conn.commit()
+            
+            # Now recreate the table without the position column
+            # 1. Create new table
+            conn.execute(text("""
+                CREATE TABLE story_items_new (
+                    id VARCHAR PRIMARY KEY,
+                    story_id VARCHAR NOT NULL,
+                    generation_id VARCHAR NOT NULL,
+                    start_time_ms INTEGER NOT NULL DEFAULT 0,
+                    created_at DATETIME,
+                    FOREIGN KEY (story_id) REFERENCES stories(id),
+                    FOREIGN KEY (generation_id) REFERENCES generations(id)
+                )
+            """))
+            
+            # 2. Copy data
+            conn.execute(text("""
+                INSERT INTO story_items_new (id, story_id, generation_id, start_time_ms, created_at)
+                SELECT id, story_id, generation_id, start_time_ms, created_at FROM story_items
+            """))
+            
+            # 3. Drop old table
+            conn.execute(text("DROP TABLE story_items"))
+            
+            # 4. Rename new table
+            conn.execute(text("ALTER TABLE story_items_new RENAME TO story_items"))
+            
+            conn.commit()
+            print("Migrated story_items table to use start_time_ms (removed position column)")
+    
+    # Migration: Add track column if it doesn't exist
+    # Re-check columns after potential position migration
+    columns = {col['name'] for col in inspector.get_columns('story_items')}
+    if 'track' not in columns:
+        print("Migrating story_items: adding track column")
+        with engine.connect() as conn:
+            conn.execute(text("ALTER TABLE story_items ADD COLUMN track INTEGER NOT NULL DEFAULT 0"))
+            conn.commit()
+            print("Added track column to story_items")
+    
+    # Migration: Add trim columns if they don't exist
+    # Re-check columns after potential track migration
+    columns = {col['name'] for col in inspector.get_columns('story_items')}
+    if 'trim_start_ms' not in columns:
+        print("Migrating story_items: adding trim_start_ms column")
+        with engine.connect() as conn:
+            conn.execute(text("ALTER TABLE story_items ADD COLUMN trim_start_ms INTEGER NOT NULL DEFAULT 0"))
+            conn.commit()
+            print("Added trim_start_ms column to story_items")
+    
+    columns = {col['name'] for col in inspector.get_columns('story_items')}
+    if 'trim_end_ms' not in columns:
+        print("Migrating story_items: adding trim_end_ms column")
+        with engine.connect() as conn:
+            conn.execute(text("ALTER TABLE story_items ADD COLUMN trim_end_ms INTEGER NOT NULL DEFAULT 0"))
+            conn.commit()
+            print("Added trim_end_ms column to story_items")
+
+    # Migration: Add avatar_path to profiles table
+    if 'profiles' in inspector.get_table_names():
+        columns = {col['name'] for col in inspector.get_columns('profiles')}
+        if 'avatar_path' not in columns:
+            print("Migrating profiles: adding avatar_path column")
+            with engine.connect() as conn:
+                conn.execute(text("ALTER TABLE profiles ADD COLUMN avatar_path VARCHAR"))
+                conn.commit()
+                print("Added avatar_path column to profiles")
+
+
 def get_db():
     """Get database session (generator for dependency injection)."""
     db = SessionLocal()

backend/export_import.py

@@ -75,6 +75,16 @@ def export_profile_to_zip(profile_id: str, db: Session) -> bytes:
     zip_buffer = io.BytesIO()
     
     with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zip_file:
+        # Check if profile has avatar
+        has_avatar = False
+        if profile.avatar_path:
+            avatar_path = Path(profile.avatar_path)
+            if avatar_path.exists():
+                has_avatar = True
+                # Add avatar to ZIP root with original extension
+                avatar_ext = avatar_path.suffix
+                zip_file.write(avatar_path, f"avatar{avatar_ext}")
+
         # Create manifest.json
         manifest = {
             "version": "1.0",
@@ -82,30 +92,31 @@ def export_profile_to_zip(profile_id: str, db: Session) -> bytes:
                 "name": profile.name,
                 "description": profile.description,
                 "language": profile.language,
-            }
+            },
+            "has_avatar": has_avatar,
         }
         zip_file.writestr("manifest.json", json.dumps(manifest, indent=2))
-        
+
         # Create samples.json mapping
         samples_data = {}
         profile_dir = _get_profiles_dir() / profile_id
-        
+
         for sample in samples:
             # Get filename from audio_path (should be {sample_id}.wav)
             audio_path = Path(sample.audio_path)
             filename = audio_path.name
-            
+
             # Read audio file
             if not audio_path.exists():
                 raise ValueError(f"Audio file not found: {audio_path}")
-            
+
             # Add to samples directory in ZIP
             zip_path = f"samples/{filename}"
             zip_file.write(audio_path, zip_path)
-            
+
             # Map filename to reference text
             samples_data[filename] = sample.reference_text
-        
+
         zip_file.writestr("samples.json", json.dumps(samples_data, indent=2))
     
     zip_buffer.seek(0)
@@ -168,11 +179,31 @@ async def import_profile_from_zip(file_bytes: bytes, db: Session) -> VoiceProfil
             )
             
             profile = await create_profile(profile_create, db)
-            
+
             # Extract and add samples
             profile_dir = _get_profiles_dir() / profile.id
             profile_dir.mkdir(parents=True, exist_ok=True)
-            
+
+            # Handle avatar if present
+            avatar_files = [f for f in namelist if f.startswith("avatar.")]
+            if avatar_files:
+                try:
+                    avatar_file = avatar_files[0]
+                    # Extract to temporary file
+                    import tempfile
+                    with tempfile.NamedTemporaryFile(suffix=Path(avatar_file).suffix, delete=False) as tmp:
+                        tmp.write(zip_file.read(avatar_file))
+                        tmp_path = tmp.name
+
+                    try:
+                        from .profiles import upload_avatar
+                        await upload_avatar(profile.id, tmp_path, db)
+                    finally:
+                        Path(tmp_path).unlink(missing_ok=True)
+                except Exception as e:
+                    # Avatar import is optional - continue even if it fails
+                    pass
+
             for filename, reference_text in samples_data.items():
                 # Validate filename
                 if not filename.endswith('.wav'):

backend/main.py

@@ -11,6 +11,7 @@ from fastapi.staticfiles import StaticFiles
 from sqlalchemy.orm import Session
 from typing import List, Optional
 from datetime import datetime
+import asyncio
 import uvicorn
 import argparse
 import torch
@@ -18,16 +19,21 @@ import tempfile
 import io
 from pathlib import Path
 import uuid
+import asyncio
+import signal
+import os
 
-from . import database, models, profiles, history, tts, transcribe, config, export_import, channels
+from . import database, models, profiles, history, tts, transcribe, config, export_import, channels, stories, __version__
 from .database import get_db, Generation as DBGeneration, VoiceProfile as DBVoiceProfile
 from .utils.progress import get_progress_manager
 from .utils.tasks import get_task_manager
+from .utils.cache import clear_voice_prompt_cache
+from .platform_detect import get_backend_type
 
 app = FastAPI(
     title="voicebox API",
     description="Production-quality Qwen3-TTS voice cloning API",
-    version="0.1.0",
+    version=__version__,
 )
 
 # CORS middleware
@@ -47,23 +53,43 @@ app.add_middleware(
 @app.get("/")
 async def root():
     """Root endpoint."""
-    return {"message": "voicebox API", "version": "0.1.4"}
+    return {"message": "voicebox API", "version": __version__}
+
+
+@app.post("/shutdown")
+async def shutdown():
+    """Gracefully shutdown the server."""
+    async def shutdown_async():
+        await asyncio.sleep(0.1)  # Give response time to send
+        os.kill(os.getpid(), signal.SIGTERM)
+
+    asyncio.create_task(shutdown_async())
+    return {"message": "Shutting down..."}
 
 
 @app.get("/health", response_model=models.HealthResponse)
 async def health():
     """Health check endpoint."""
-    from huggingface_hub import hf_hub_download
+    from huggingface_hub import hf_hub_download, constants as hf_constants
     from pathlib import Path
     import os
-    
+
     tts_model = tts.get_tts_model()
+    backend_type = get_backend_type()
 
     # Check for GPU availability (CUDA or MPS)
     has_cuda = torch.cuda.is_available()
     has_mps = hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()
     gpu_available = has_cuda or has_mps
 
+    gpu_type = None
+    if has_cuda:
+        gpu_type = f"CUDA ({torch.cuda.get_device_name(0)})"
+    elif has_mps:
+        gpu_type = "MPS (Apple Silicon)"
+    elif backend_type == "mlx":
+        gpu_type = "Metal (Apple Silicon via MLX)"
+
     vram_used = None
     if has_cuda:
         vram_used = torch.cuda.memory_allocated() / 1024 / 1024  # MB
@@ -90,7 +116,11 @@ async def health():
     model_downloaded = None
     try:
         # Check if the default model (1.7B) is cached
-        default_model_id = "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
+        # Use different model IDs based on backend
+        if backend_type == "mlx":
+            default_model_id = "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16"
+        else:
+            default_model_id = "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
         
         # Method 1: Try scan_cache_dir if available
         try:
@@ -101,15 +131,16 @@ async def health():
                     model_downloaded = True
                     break
         except (ImportError, Exception):
-            # Method 2: Check cache directory
-            cache_dir = os.path.expanduser("~/.cache/huggingface/hub")
-            repo_cache = Path(cache_dir) / "models--" + default_model_id.replace("/", "--")
+            # Method 2: Check cache directory (using HuggingFace's OS-specific cache location)
+            cache_dir = hf_constants.HF_HUB_CACHE
+            repo_cache = Path(cache_dir) / ("models--" + default_model_id.replace("/", "--"))
             if repo_cache.exists():
                 has_model_files = (
                     any(repo_cache.rglob("*.bin")) or
                     any(repo_cache.rglob("*.safetensors")) or
                     any(repo_cache.rglob("*.pt")) or
-                    any(repo_cache.rglob("*.pth"))
+                    any(repo_cache.rglob("*.pth")) or
+                    any(repo_cache.rglob("*.npz"))  # MLX models may use npz
                 )
                 model_downloaded = has_model_files
     except Exception:
@@ -121,7 +152,9 @@ async def health():
         model_downloaded=model_downloaded,
         model_size=model_size,
         gpu_available=gpu_available,
+        gpu_type=gpu_type,
         vram_used_mb=vram_used,
+        backend_type=backend_type,
     )
 
 
@@ -261,6 +294,74 @@ async def delete_profile_sample(
     return {"message": "Sample deleted successfully"}
 
 
+@app.put("/profiles/samples/{sample_id}", response_model=models.ProfileSampleResponse)
+async def update_profile_sample(
+    sample_id: str,
+    data: models.ProfileSampleUpdate,
+    db: Session = Depends(get_db),
+):
+    """Update a profile sample's reference text."""
+    sample = await profiles.update_profile_sample(sample_id, data.reference_text, db)
+    if not sample:
+        raise HTTPException(status_code=404, detail="Sample not found")
+    return sample
+
+
+@app.post("/profiles/{profile_id}/avatar", response_model=models.VoiceProfileResponse)
+async def upload_profile_avatar(
+    profile_id: str,
+    file: UploadFile = File(...),
+    db: Session = Depends(get_db),
+):
+    """Upload or update avatar image for a profile."""
+    # Save uploaded file to temp location
+    with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as tmp:
+        content = await file.read()
+        tmp.write(content)
+        tmp_path = tmp.name
+
+    try:
+        profile = await profiles.upload_avatar(profile_id, tmp_path, db)
+        return profile
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    finally:
+        # Clean up temp file
+        Path(tmp_path).unlink(missing_ok=True)
+
+
+@app.get("/profiles/{profile_id}/avatar")
+async def get_profile_avatar(
+    profile_id: str,
+    db: Session = Depends(get_db),
+):
+    """Get avatar image for a profile."""
+    profile = await profiles.get_profile(profile_id, db)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Profile not found")
+
+    if not profile.avatar_path:
+        raise HTTPException(status_code=404, detail="No avatar found for this profile")
+
+    avatar_path = Path(profile.avatar_path)
+    if not avatar_path.exists():
+        raise HTTPException(status_code=404, detail="Avatar file not found")
+
+    return FileResponse(avatar_path)
+
+
+@app.delete("/profiles/{profile_id}/avatar")
+async def delete_profile_avatar(
+    profile_id: str,
+    db: Session = Depends(get_db),
+):
+    """Delete avatar image for a profile."""
+    success = await profiles.delete_avatar(profile_id, db)
+    if not success:
+        raise HTTPException(status_code=404, detail="Profile not found or no avatar to delete")
+    return {"message": "Avatar deleted successfully"}
+
+
 @app.get("/profiles/{profile_id}/export")
 async def export_profile(
     profile_id: str,
@@ -451,6 +552,36 @@ async def generate_speech(
         tts_model = tts.get_tts_model()
         # Load the requested model size if different from current (async to not block)
         model_size = data.model_size or "1.7B"
+
+        # Check if model needs to be downloaded first
+        model_path = tts_model._get_model_path(model_size)
+        if model_path.startswith("Qwen/"):
+            # Model not cached - check if it exists remotely or needs download
+            from huggingface_hub import constants as hf_constants
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_path.replace("/", "--"))
+            if not repo_cache.exists():
+                # Start download in background
+                model_name = f"qwen-tts-{model_size}"
+
+                async def download_model_background():
+                    try:
+                        await tts_model.load_model_async(model_size)
+                    except Exception as e:
+                        task_manager.error_download(model_name, str(e))
+
+                task_manager.start_download(model_name)
+                asyncio.create_task(download_model_background())
+
+                # Return 202 Accepted with download info
+                raise HTTPException(
+                    status_code=202,
+                    detail={
+                        "message": f"Model {model_size} is being downloaded. Please wait and try again.",
+                        "model_name": model_name,
+                        "downloading": True
+                    }
+                )
+
         await tts_model.load_model_async(model_size)
         audio, sample_rate = await tts_model.generate(
             data.text,
@@ -684,6 +815,37 @@ async def transcribe_audio(
         
         # Transcribe
         whisper_model = transcribe.get_whisper_model()
+
+        # Check if Whisper model is downloaded (uses default size "base")
+        model_size = whisper_model.model_size
+        model_name = f"openai/whisper-{model_size}"
+
+        # Check if model is cached
+        from huggingface_hub import constants as hf_constants
+        repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_name.replace("/", "--"))
+        if not repo_cache.exists():
+            # Start download in background
+            progress_model_name = f"whisper-{model_size}"
+
+            async def download_whisper_background():
+                try:
+                    await whisper_model.load_model_async(model_size)
+                except Exception as e:
+                    get_task_manager().error_download(progress_model_name, str(e))
+
+            get_task_manager().start_download(progress_model_name)
+            asyncio.create_task(download_whisper_background())
+
+            # Return 202 Accepted
+            raise HTTPException(
+                status_code=202,
+                detail={
+                    "message": f"Whisper model {model_size} is being downloaded. Please wait and try again.",
+                    "model_name": progress_model_name,
+                    "downloading": True
+                }
+            )
+
         text = await whisper_model.transcribe(tmp_path, language)
         
         return models.TranscriptionResponse(
@@ -698,6 +860,209 @@ async def transcribe_audio(
         Path(tmp_path).unlink(missing_ok=True)
 
 
+# ============================================
+# STORY ENDPOINTS
+# ============================================
+
+@app.get("/stories", response_model=List[models.StoryResponse])
+async def list_stories(db: Session = Depends(get_db)):
+    """List all stories."""
+    return await stories.list_stories(db)
+
+
+@app.post("/stories", response_model=models.StoryResponse)
+async def create_story(
+    data: models.StoryCreate,
+    db: Session = Depends(get_db),
+):
+    """Create a new story."""
+    try:
+        return await stories.create_story(data, db)
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@app.get("/stories/{story_id}", response_model=models.StoryDetailResponse)
+async def get_story(
+    story_id: str,
+    db: Session = Depends(get_db),
+):
+    """Get a story with all its items."""
+    story = await stories.get_story(story_id, db)
+    if not story:
+        raise HTTPException(status_code=404, detail="Story not found")
+    return story
+
+
+@app.put("/stories/{story_id}", response_model=models.StoryResponse)
+async def update_story(
+    story_id: str,
+    data: models.StoryCreate,
+    db: Session = Depends(get_db),
+):
+    """Update a story."""
+    story = await stories.update_story(story_id, data, db)
+    if not story:
+        raise HTTPException(status_code=404, detail="Story not found")
+    return story
+
+
+@app.delete("/stories/{story_id}")
+async def delete_story(
+    story_id: str,
+    db: Session = Depends(get_db),
+):
+    """Delete a story."""
+    success = await stories.delete_story(story_id, db)
+    if not success:
+        raise HTTPException(status_code=404, detail="Story not found")
+    return {"message": "Story deleted successfully"}
+
+
+@app.post("/stories/{story_id}/items", response_model=models.StoryItemDetail)
+async def add_story_item(
+    story_id: str,
+    data: models.StoryItemCreate,
+    db: Session = Depends(get_db),
+):
+    """Add a generation to a story."""
+    item = await stories.add_item_to_story(story_id, data, db)
+    if not item:
+        raise HTTPException(status_code=404, detail="Story or generation not found")
+    return item
+
+
+@app.delete("/stories/{story_id}/items/{item_id}")
+async def remove_story_item(
+    story_id: str,
+    item_id: str,
+    db: Session = Depends(get_db),
+):
+    """Remove a story item from a story."""
+    success = await stories.remove_item_from_story(story_id, item_id, db)
+    if not success:
+        raise HTTPException(status_code=404, detail="Story item not found")
+    return {"message": "Item removed successfully"}
+
+
+@app.put("/stories/{story_id}/items/times")
+async def update_story_item_times(
+    story_id: str,
+    data: models.StoryItemBatchUpdate,
+    db: Session = Depends(get_db),
+):
+    """Update story item timecodes."""
+    success = await stories.update_story_item_times(story_id, data, db)
+    if not success:
+        raise HTTPException(status_code=400, detail="Invalid timecode update request")
+    return {"message": "Item timecodes updated successfully"}
+
+
+@app.put("/stories/{story_id}/items/reorder", response_model=List[models.StoryItemDetail])
+async def reorder_story_items(
+    story_id: str,
+    data: models.StoryItemReorder,
+    db: Session = Depends(get_db),
+):
+    """Reorder story items and recalculate timecodes."""
+    items = await stories.reorder_story_items(story_id, data.generation_ids, db)
+    if items is None:
+        raise HTTPException(status_code=400, detail="Invalid reorder request - ensure all generation IDs belong to this story")
+    return items
+
+
+@app.put("/stories/{story_id}/items/{item_id}/move", response_model=models.StoryItemDetail)
+async def move_story_item(
+    story_id: str,
+    item_id: str,
+    data: models.StoryItemMove,
+    db: Session = Depends(get_db),
+):
+    """Move a story item (update position and/or track)."""
+    item = await stories.move_story_item(story_id, item_id, data, db)
+    if item is None:
+        raise HTTPException(status_code=404, detail="Story item not found")
+    return item
+
+
+@app.put("/stories/{story_id}/items/{item_id}/trim", response_model=models.StoryItemDetail)
+async def trim_story_item(
+    story_id: str,
+    item_id: str,
+    data: models.StoryItemTrim,
+    db: Session = Depends(get_db),
+):
+    """Trim a story item (update trim_start_ms and trim_end_ms)."""
+    item = await stories.trim_story_item(story_id, item_id, data, db)
+    if item is None:
+        raise HTTPException(status_code=404, detail="Story item not found or invalid trim values")
+    return item
+
+
+@app.post("/stories/{story_id}/items/{item_id}/split", response_model=List[models.StoryItemDetail])
+async def split_story_item(
+    story_id: str,
+    item_id: str,
+    data: models.StoryItemSplit,
+    db: Session = Depends(get_db),
+):
+    """Split a story item at a given time, creating two clips."""
+    items = await stories.split_story_item(story_id, item_id, data, db)
+    if items is None:
+        raise HTTPException(status_code=404, detail="Story item not found or invalid split point")
+    return items
+
+
+@app.post("/stories/{story_id}/items/{item_id}/duplicate", response_model=models.StoryItemDetail)
+async def duplicate_story_item(
+    story_id: str,
+    item_id: str,
+    db: Session = Depends(get_db),
+):
+    """Duplicate a story item, creating a copy with all properties."""
+    item = await stories.duplicate_story_item(story_id, item_id, db)
+    if item is None:
+        raise HTTPException(status_code=404, detail="Story item not found")
+    return item
+
+
+@app.get("/stories/{story_id}/export-audio")
+async def export_story_audio(
+    story_id: str,
+    db: Session = Depends(get_db),
+):
+    """Export story as single mixed audio file with timecode-based mixing."""
+    try:
+        # Get story to create filename
+        story = db.query(database.Story).filter_by(id=story_id).first()
+        if not story:
+            raise HTTPException(status_code=404, detail="Story not found")
+        
+        # Export audio
+        audio_bytes = await stories.export_story_audio(story_id, db)
+        if not audio_bytes:
+            raise HTTPException(status_code=400, detail="Story has no audio items")
+        
+        # Create safe filename
+        safe_name = "".join(c for c in story.name if c.isalnum() or c in (' ', '-', '_')).strip()
+        if not safe_name:
+            safe_name = "story"
+        filename = f"{safe_name}.wav"
+        
+        # Return as streaming response
+        return StreamingResponse(
+            io.BytesIO(audio_bytes),
+            media_type="audio/wav",
+            headers={
+                "Content-Disposition": f'attachment; filename="{filename}"'
+            }
+        )
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
 # ============================================
 # FILE SERVING
 # ============================================
@@ -791,9 +1156,14 @@ async def get_model_progress(model_name: str):
 @app.get("/models/status", response_model=models.ModelStatusListResponse)
 async def get_model_status():
     """Get status of all available models."""
-    from huggingface_hub import hf_hub_download
+    from huggingface_hub import constants as hf_constants
     from pathlib import Path
-    import os
+    
+    backend_type = get_backend_type()
+    task_manager = get_task_manager()
+    
+    # Get set of currently downloading model names
+    active_download_names = {task.model_name for task in task_manager.get_active_downloads()}
     
     # Try to import scan_cache_dir (might not be available in older versions)
     try:
@@ -806,7 +1176,7 @@ async def get_model_status():
         """Check if TTS model is loaded with specific size."""
         try:
             tts_model = tts.get_tts_model()
-            return tts_model.is_loaded() and tts_model.model_size == model_size
+            return tts_model.is_loaded() and getattr(tts_model, 'model_size', None) == model_size
         except Exception:
             return False
     
@@ -814,55 +1184,79 @@ async def get_model_status():
         """Check if Whisper model is loaded with specific size."""
         try:
             whisper_model = transcribe.get_whisper_model()
-            return whisper_model.is_loaded() and whisper_model.model_size == model_size
+            return whisper_model.is_loaded() and getattr(whisper_model, 'model_size', None) == model_size
         except Exception:
             return False
     
+    # Use backend-specific model IDs
+    if backend_type == "mlx":
+        tts_1_7b_id = "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16"
+        tts_0_6b_id = "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16"  # Fallback to 1.7B
+        # MLX backend uses openai/whisper-* models, not mlx-community
+        whisper_base_id = "openai/whisper-base"
+        whisper_small_id = "openai/whisper-small"
+        whisper_medium_id = "openai/whisper-medium"
+        whisper_large_id = "openai/whisper-large"
+    else:
+        tts_1_7b_id = "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
+        tts_0_6b_id = "Qwen/Qwen3-TTS-12Hz-0.6B-Base"
+        whisper_base_id = "openai/whisper-base"
+        whisper_small_id = "openai/whisper-small"
+        whisper_medium_id = "openai/whisper-medium"
+        whisper_large_id = "openai/whisper-large"
+    
     model_configs = [
         {
             "model_name": "qwen-tts-1.7B",
             "display_name": "Qwen TTS 1.7B",
-            "hf_repo_id": "Qwen/Qwen3-TTS-12Hz-1.7B-Base",
+            "hf_repo_id": tts_1_7b_id,
             "model_size": "1.7B",
             "check_loaded": lambda: check_tts_loaded("1.7B"),
         },
         {
             "model_name": "qwen-tts-0.6B",
             "display_name": "Qwen TTS 0.6B",
-            "hf_repo_id": "Qwen/Qwen3-TTS-12Hz-0.6B-Base",
+            "hf_repo_id": tts_0_6b_id,
             "model_size": "0.6B",
             "check_loaded": lambda: check_tts_loaded("0.6B"),
         },
         {
             "model_name": "whisper-base",
             "display_name": "Whisper Base",
-            "hf_repo_id": "openai/whisper-base",
+            "hf_repo_id": whisper_base_id,
             "model_size": "base",
             "check_loaded": lambda: check_whisper_loaded("base"),
         },
         {
             "model_name": "whisper-small",
             "display_name": "Whisper Small",
-            "hf_repo_id": "openai/whisper-small",
+            "hf_repo_id": whisper_small_id,
             "model_size": "small",
             "check_loaded": lambda: check_whisper_loaded("small"),
         },
         {
             "model_name": "whisper-medium",
             "display_name": "Whisper Medium",
-            "hf_repo_id": "openai/whisper-medium",
+            "hf_repo_id": whisper_medium_id,
             "model_size": "medium",
             "check_loaded": lambda: check_whisper_loaded("medium"),
         },
         {
             "model_name": "whisper-large",
             "display_name": "Whisper Large",
-            "hf_repo_id": "openai/whisper-large",
+            "hf_repo_id": whisper_large_id,
             "model_size": "large",
             "check_loaded": lambda: check_whisper_loaded("large"),
         },
     ]
     
+    # Build a mapping of model_name -> hf_repo_id so we can check if shared repos are downloading
+    model_to_repo = {cfg["model_name"]: cfg["hf_repo_id"] for cfg in model_configs}
+    
+    # Get the set of hf_repo_ids that are currently being downloaded
+    # This handles the case where multiple models share the same repo (e.g., 0.6B and 1.7B on MLX)
+    active_download_repos = {model_to_repo.get(name) for name in active_download_names if name in model_to_repo}
+    
     # Get HuggingFace cache info (if available)
     cache_info = None
     if use_scan_cache:
@@ -885,56 +1279,80 @@ async def get_model_status():
                 repo_id = config["hf_repo_id"]
                 for repo in cache_info.repos:
                     if repo.repo_id == repo_id:
-                        downloaded = True
-                        # Calculate size from cache info
+                        # Check if actual model weight files exist (not just config files)
+                        # scan_cache_dir only shows completed files, so check if any are model weights
+                        has_model_weights = False
+                        for rev in repo.revisions:
+                            for f in rev.files:
+                                fname = f.file_name.lower()
+                                if fname.endswith(('.safetensors', '.bin', '.pt', '.pth', '.npz')):
+                                    has_model_weights = True
+                                    break
+                            if has_model_weights:
+                                break
+                        
+                        # Also check for .incomplete files in blobs directory (downloads in progress)
+                        has_incomplete = False
                         try:
-                            total_size = sum(revision.size_on_disk for revision in repo.revisions)
-                            size_mb = total_size / (1024 * 1024)
+                            cache_dir = hf_constants.HF_HUB_CACHE
+                            blobs_dir = Path(cache_dir) / ("models--" + repo_id.replace("/", "--")) / "blobs"
+                            if blobs_dir.exists():
+                                has_incomplete = any(blobs_dir.glob("*.incomplete"))
                         except Exception:
                             pass
-                        break
-            
-            # Method 2: Fallback to checking cache directory directly
-            if not downloaded:
-                try:
-                    cache_dir = os.path.expanduser("~/.cache/huggingface/hub")
-                    repo_cache = Path(cache_dir) / "models--" + config["hf_repo_id"].replace("/", "--")
-                    
-                    if repo_cache.exists():
-                        # Check for model files (bin, safetensors, or other common model files)
-                        has_model_files = (
-                            any(repo_cache.rglob("*.bin")) or
-                            any(repo_cache.rglob("*.safetensors")) or
-                            any(repo_cache.rglob("*.pt")) or
-                            any(repo_cache.rglob("*.pth")) or
-                            any(repo_cache.rglob("model.safetensors.index.json")) or
-                            any(repo_cache.rglob("pytorch_model.bin.index.json"))
-                        )
                         
-                        if has_model_files:
+                        # Only mark as downloaded if we have model weights AND no incomplete files
+                        if has_model_weights and not has_incomplete:
                             downloaded = True
-                            # Calculate size
+                            # Calculate size from cache info
                             try:
-                                total_size = sum(f.stat().st_size for f in repo_cache.rglob("*") if f.is_file())
+                                total_size = sum(revision.size_on_disk for revision in repo.revisions)
                                 size_mb = total_size / (1024 * 1024)
                             except Exception:
                                 pass
+                        break
+            
+            # Method 2: Fallback to checking cache directory directly (using HuggingFace's OS-specific cache location)
+            if not downloaded:
+                try:
+                    cache_dir = hf_constants.HF_HUB_CACHE
+                    repo_cache = Path(cache_dir) / ("models--" + config["hf_repo_id"].replace("/", "--"))
+                    
+                    if repo_cache.exists():
+                        # Check for .incomplete files - if any exist, download is still in progress
+                        blobs_dir = repo_cache / "blobs"
+                        has_incomplete = blobs_dir.exists() and any(blobs_dir.glob("*.incomplete"))
+                        
+                        if not has_incomplete:
+                            # Check for actual model weight files (not just index files)
+                            # in the snapshots directory (symlinks to completed blobs)
+                            snapshots_dir = repo_cache / "snapshots"
+                            has_model_files = False
+                            if snapshots_dir.exists():
+                                has_model_files = (
+                                    any(snapshots_dir.rglob("*.bin")) or
+                                    any(snapshots_dir.rglob("*.safetensors")) or
+                                    any(snapshots_dir.rglob("*.pt")) or
+                                    any(snapshots_dir.rglob("*.pth")) or
+                                    any(snapshots_dir.rglob("*.npz"))
+                                )
+                            
+                            if has_model_files:
+                                downloaded = True
+                                # Calculate size (exclude .incomplete files)
+                                try:
+                                    total_size = sum(
+                                        f.stat().st_size for f in repo_cache.rglob("*") 
+                                        if f.is_file() and not f.name.endswith('.incomplete')
+                                    )
+                                    size_mb = total_size / (1024 * 1024)
+                                except Exception:
+                                    pass
                 except Exception:
                     pass
             
-            # Method 3: Try to check if model can be loaded locally (last resort)
-            if not downloaded:
-                try:
-                    # Try to download with local_files_only=True to check if cached
-                    hf_hub_download(
-                        repo_id=config["hf_repo_id"],
-                        filename="config.json",  # Try a common file
-                        local_files_only=True,
-                    )
-                    downloaded = True
-                except Exception:
-                    # File not found locally, model not downloaded
-                    pass
+            # Method 3 removed - checking for config.json is too lenient
+            # Methods 1 and 2 properly verify that model weight files exist
             
             # Check if loaded in memory
             try:
@@ -942,10 +1360,19 @@ async def get_model_status():
             except Exception:
                 loaded = False
             
+            # Check if this model (or its shared repo) is currently being downloaded
+            is_downloading = config["hf_repo_id"] in active_download_repos
+            
+            # If downloading, don't report as downloaded (partial files exist)
+            if is_downloading:
+                downloaded = False
+                size_mb = None  # Don't show partial size during download
+            
             statuses.append(models.ModelStatus(
                 model_name=config["model_name"],
                 display_name=config["display_name"],
                 downloaded=downloaded,
+                downloading=is_downloading,
                 size_mb=size_mb,
                 loaded=loaded,
             ))
@@ -956,10 +1383,14 @@ async def get_model_status():
             except Exception:
                 loaded = False
             
+            # Check if this model (or its shared repo) is currently being downloaded
+            is_downloading = config["hf_repo_id"] in active_download_repos
+            
             statuses.append(models.ModelStatus(
                 model_name=config["model_name"],
                 display_name=config["display_name"],
                 downloaded=False,  # Assume not downloaded if check failed
+                downloading=is_downloading,
                 size_mb=None,
                 loaded=loaded,
             ))
@@ -973,6 +1404,7 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
     import asyncio
     
     task_manager = get_task_manager()
+    progress_manager = get_progress_manager()
     
     model_configs = {
         "qwen-tts-1.7B": {
@@ -1006,22 +1438,38 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
     
     config = model_configs[request.model_name]
     
-    try:
-        # Start tracking download
-        task_manager.start_download(request.model_name)
-        
-        # Trigger download by loading the model (which will download if not cached)
-        # Run in background to avoid blocking
-        await asyncio.to_thread(config["load_func"])
-        
-        # Mark download as complete
-        task_manager.complete_download(request.model_name)
-        
-        return {"message": f"Model {request.model_name} download started"}
-    except Exception as e:
-        # Mark download as failed
-        task_manager.error_download(request.model_name, str(e))
-        raise HTTPException(status_code=500, detail=str(e))
+    async def download_in_background():
+        """Download model in background without blocking the HTTP request."""
+        try:
+            # Call the load function (which may be async)
+            result = config["load_func"]()
+            # If it's a coroutine, await it
+            if asyncio.iscoroutine(result):
+                await result
+            task_manager.complete_download(request.model_name)
+        except Exception as e:
+            task_manager.error_download(request.model_name, str(e))
+
+    # Start tracking download
+    task_manager.start_download(request.model_name)
+    
+    # Initialize progress state so SSE endpoint has initial data to send.
+    # This fixes a race condition where the frontend connects to SSE before
+    # any progress callbacks have fired (especially for large models like Qwen
+    # where huggingface_hub takes time to fetch metadata for all files).
+    progress_manager.update_progress(
+        model_name=request.model_name,
+        current=0,
+        total=0,  # Will be updated once actual total is known
+        filename="Connecting to HuggingFace...",
+        status="downloading",
+    )
+
+    # Start download in background task (don't await)
+    asyncio.create_task(download_in_background())
+
+    # Return immediately - frontend should poll progress endpoint
+    return {"message": f"Model {request.model_name} download started"}
 
 
 @app.delete("/models/{model_name}")
@@ -1029,6 +1477,7 @@ async def delete_model(model_name: str):
     """Delete a downloaded model from the HuggingFace cache."""
     import shutil
     import os
+    from huggingface_hub import constants as hf_constants
     
     # Map model names to HuggingFace repo IDs
     model_configs = {
@@ -1081,8 +1530,8 @@ async def delete_model(model_name: str):
             if whisper_model.is_loaded() and whisper_model.model_size == config["model_size"]:
                 transcribe.unload_whisper_model()
         
-        # Find and delete the cache directory
-        cache_dir = os.path.expanduser("~/.cache/huggingface/hub")
+        # Find and delete the cache directory (using HuggingFace's OS-specific cache location)
+        cache_dir = hf_constants.HF_HUB_CACHE
         repo_cache_dir = Path(cache_dir) / ("models--" + hf_repo_id.replace("/", "--"))
         
         # Check if the cache directory exists
@@ -1106,6 +1555,19 @@ async def delete_model(model_name: str):
         raise HTTPException(status_code=500, detail=f"Failed to delete model: {str(e)}")
 
 
+@app.post("/cache/clear")
+async def clear_cache():
+    """Clear all voice prompt caches (memory and disk)."""
+    try:
+        deleted_count = clear_voice_prompt_cache()
+        return {
+            "message": f"Voice prompt cache cleared successfully",
+            "files_deleted": deleted_count,
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to clear cache: {str(e)}")
+
+
 # ============================================
 # TASK MANAGEMENT
 # ============================================
@@ -1178,10 +1640,13 @@ async def get_active_tasks():
 
 def _get_gpu_status() -> str:
     """Get GPU availability status."""
+    backend_type = get_backend_type()
     if torch.cuda.is_available():
         return f"CUDA ({torch.cuda.get_device_name(0)})"
     elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
         return "MPS (Apple Silicon)"
+    elif backend_type == "mlx":
+        return "Metal (Apple Silicon via MLX)"
     return "None (CPU only)"
 
 
@@ -1191,8 +1656,28 @@ async def startup_event():
     print("voicebox API starting up...")
     database.init_db()
     print(f"Database initialized at {database._db_path}")
+    backend_type = get_backend_type()
+    print(f"Backend: {backend_type.upper()}")
     print(f"GPU available: {_get_gpu_status()}")
 
+    # Initialize progress manager with main event loop for thread-safe operations
+    try:
+        progress_manager = get_progress_manager()
+        progress_manager._set_main_loop(asyncio.get_running_loop())
+        print("Progress manager initialized with event loop")
+    except Exception as e:
+        print(f"Warning: Could not initialize progress manager event loop: {e}")
+
+    # Ensure HuggingFace cache directory exists
+    try:
+        from huggingface_hub import constants as hf_constants
+        cache_dir = Path(hf_constants.HF_HUB_CACHE)
+        cache_dir.mkdir(parents=True, exist_ok=True)
+        print(f"HuggingFace cache directory: {cache_dir}")
+    except Exception as e:
+        print(f"Warning: Could not create HuggingFace cache directory: {e}")
+        print("Model downloads may fail. Please ensure the directory exists and has write permissions.")
+
 
 @app.on_event("shutdown")
 async def shutdown_event():

backend/models.py

@@ -20,6 +20,7 @@ class VoiceProfileResponse(BaseModel):
     name: str
     description: Optional[str]
     language: str
+    avatar_path: Optional[str] = None
     created_at: datetime
     updated_at: datetime
 
@@ -32,6 +33,11 @@ class ProfileSampleCreate(BaseModel):
     reference_text: str = Field(..., min_length=1, max_length=1000)
 
 
+class ProfileSampleUpdate(BaseModel):
+    """Request model for updating a profile sample."""
+    reference_text: str = Field(..., min_length=1, max_length=1000)
+
+
 class ProfileSampleResponse(BaseModel):
     """Response model for profile sample."""
     id: str
@@ -118,7 +124,9 @@ class HealthResponse(BaseModel):
     model_downloaded: Optional[bool] = None  # Whether model is cached/downloaded
     model_size: Optional[str] = None  # Current model size if loaded
     gpu_available: bool
+    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)
 
 
 class ModelStatus(BaseModel):
@@ -126,6 +134,7 @@ class ModelStatus(BaseModel):
     model_name: str
     display_name: str
     downloaded: bool
+    downloading: bool = False  # True if download is in progress
     size_mb: Optional[float] = None
     loaded: bool = False
 
@@ -193,3 +202,100 @@ class ChannelVoiceAssignment(BaseModel):
 class ProfileChannelAssignment(BaseModel):
     """Request model for assigning channels to a profile."""
     channel_ids: List[str]
+
+
+class StoryCreate(BaseModel):
+    """Request model for creating a story."""
+    name: str = Field(..., min_length=1, max_length=100)
+    description: Optional[str] = Field(None, max_length=500)
+
+
+class StoryResponse(BaseModel):
+    """Response model for story (list view)."""
+    id: str
+    name: str
+    description: Optional[str]
+    created_at: datetime
+    updated_at: datetime
+    item_count: int = 0
+
+    class Config:
+        from_attributes = True
+
+
+class StoryItemDetail(BaseModel):
+    """Detail model for story item with generation info."""
+    id: str
+    story_id: str
+    generation_id: str
+    start_time_ms: int
+    track: int = 0
+    trim_start_ms: int = 0
+    trim_end_ms: int = 0
+    created_at: datetime
+    # Generation details
+    profile_id: str
+    profile_name: str
+    text: str
+    language: str
+    audio_path: str
+    duration: float
+    seed: Optional[int]
+    instruct: Optional[str]
+    generation_created_at: datetime
+
+    class Config:
+        from_attributes = True
+
+
+class StoryDetailResponse(BaseModel):
+    """Response model for story with items."""
+    id: str
+    name: str
+    description: Optional[str]
+    created_at: datetime
+    updated_at: datetime
+    items: List[StoryItemDetail] = []
+
+    class Config:
+        from_attributes = True
+
+
+class StoryItemCreate(BaseModel):
+    """Request model for adding a generation to a story."""
+    generation_id: str
+    start_time_ms: Optional[int] = None  # If not provided, will be calculated automatically
+    track: Optional[int] = 0  # Track number (0 = main track)
+
+
+class StoryItemUpdateTime(BaseModel):
+    """Request model for updating a story item's timecode."""
+    generation_id: str
+    start_time_ms: int = Field(..., ge=0)
+
+
+class StoryItemBatchUpdate(BaseModel):
+    """Request model for batch updating story item timecodes."""
+    updates: List[StoryItemUpdateTime]
+
+
+class StoryItemReorder(BaseModel):
+    """Request model for reordering story items."""
+    generation_ids: List[str] = Field(..., min_length=1)
+
+
+class StoryItemMove(BaseModel):
+    """Request model for moving a story item (position and/or track)."""
+    start_time_ms: int = Field(..., ge=0)
+    track: int = 0
+
+
+class StoryItemTrim(BaseModel):
+    """Request model for trimming a story item."""
+    trim_start_ms: int = Field(..., ge=0)
+    trim_end_ms: int = Field(..., ge=0)
+
+
+class StoryItemSplit(BaseModel):
+    """Request model for splitting a story item."""
+    split_time_ms: int = Field(..., ge=0)  # Time within the clip to split at (relative to clip start)

backend/platform_detect.py

@@ -0,0 +1,33 @@
+"""
+Platform detection for backend selection.
+"""
+
+import platform
+from typing import Literal
+
+
+def is_apple_silicon() -> bool:
+    """
+    Check if running on Apple Silicon (arm64 macOS).
+    
+    Returns:
+        True if on Apple Silicon, False otherwise
+    """
+    return platform.system() == "Darwin" and platform.machine() == "arm64"
+
+
+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
+    """
+    if is_apple_silicon():
+        try:
+            import mlx
+            return "mlx"
+        except ImportError:
+            # MLX not installed, fallback to PyTorch
+            return "pytorch"
+    return "pytorch"

backend/profiles.py

@@ -21,6 +21,8 @@ from .database import (
     ProfileSample as DBProfileSample,
 )
 from .utils.audio import validate_reference_audio, load_audio, save_audio
+from .utils.images import validate_image, process_avatar
+from .utils.cache import _get_cache_dir, clear_profile_cache
 from .tts import get_tts_model
 from . import config
 
@@ -119,6 +121,10 @@ async def add_profile_sample(
     db.commit()
     db.refresh(db_sample)
     
+    # Invalidate combined audio cache for this profile
+    # Since a new sample was added, any cached combined audio is now stale
+    clear_profile_cache(profile_id)
+    
     return ProfileSampleResponse.model_validate(db_sample)
 
 
@@ -240,6 +246,9 @@ async def delete_profile(
     if profile_dir.exists():
         shutil.rmtree(profile_dir)
     
+    # Clean up combined audio cache files for this profile
+    clear_profile_cache(profile_id)
+    
     return True
 
 
@@ -261,6 +270,9 @@ async def delete_profile_sample(
     if not sample:
         return False
     
+    # Store profile_id before deleting
+    profile_id = sample.profile_id
+    
     # Delete audio file
     audio_path = Path(sample.audio_path)
     if audio_path.exists():
@@ -270,9 +282,47 @@ async def delete_profile_sample(
     db.delete(sample)
     db.commit()
     
+    # Invalidate combined audio cache for this profile
+    # Since the sample set changed, any cached combined audio is now stale
+    clear_profile_cache(profile_id)
+    
     return True
 
 
+async def update_profile_sample(
+    sample_id: str,
+    reference_text: str,
+    db: Session,
+) -> Optional[ProfileSampleResponse]:
+    """
+    Update a profile sample's reference text.
+    
+    Args:
+        sample_id: Sample ID
+        reference_text: Updated reference text
+        db: Database session
+        
+    Returns:
+        Updated sample or None if not found
+    """
+    sample = db.query(DBProfileSample).filter_by(id=sample_id).first()
+    if not sample:
+        return None
+    
+    # Store profile_id before updating
+    profile_id = sample.profile_id
+    
+    sample.reference_text = reference_text
+    db.commit()
+    db.refresh(sample)
+    
+    # Invalidate combined audio cache for this profile
+    # Since the reference text changed, cache keys and combined text are now stale
+    clear_profile_cache(profile_id)
+    
+    return ProfileSampleResponse.model_validate(sample)
+
+
 async def create_voice_prompt_for_profile(
     profile_id: str,
     db: Session,
@@ -280,23 +330,23 @@ async def create_voice_prompt_for_profile(
 ) -> dict:
     """
     Create a combined voice prompt from all samples in a profile.
-    
+
     Args:
         profile_id: Profile ID
         db: Database session
         use_cache: Whether to use cached prompts
-        
+
     Returns:
         Voice prompt dictionary
     """
     # 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()
-    
+
     if len(samples) == 1:
         # Single sample - use directly
         sample = samples[0]
@@ -310,27 +360,127 @@ async def create_voice_prompt_for_profile(
         # Multiple samples - combine them
         audio_paths = [s.audio_path for s in samples]
         reference_texts = [s.reference_text for s in samples]
-        
+
         # Combine audio
         combined_audio, combined_text = await tts_model.combine_voice_prompts(
             audio_paths,
             reference_texts,
         )
+
+        # Save combined audio to cache directory (persistent)
+        # Create a hash of sample IDs to identify this specific combination
+        import hashlib
+        sample_ids_str = "-".join(sorted([s.id for s in samples]))
+        combination_hash = hashlib.md5(sample_ids_str.encode()).hexdigest()[:12]
         
-        # Save combined audio temporarily
-        import tempfile
-        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
-            save_audio(combined_audio, tmp.name, 24000)
-            tmp_path = tmp.name
+        # Store in cache directory
+        cache_dir = _get_cache_dir()
+        cache_dir.mkdir(parents=True, exist_ok=True)
+        combined_path = cache_dir / f"combined_{profile_id}_{combination_hash}.wav"
         
-        try:
-            # Create prompt from combined audio
-            voice_prompt, _ = await tts_model.create_voice_prompt(
-                tmp_path,
-                combined_text,
-                use_cache=use_cache,
-            )
-            return voice_prompt
-        finally:
-            # Clean up temp file
-            Path(tmp_path).unlink(missing_ok=True)
+        # Save combined audio
+        save_audio(combined_audio, str(combined_path), 24000)
+
+        # Create prompt from combined audio
+        voice_prompt, _ = await tts_model.create_voice_prompt(
+            str(combined_path),
+            combined_text,
+            use_cache=use_cache,
+        )
+        return voice_prompt
+
+
+async def upload_avatar(
+    profile_id: str,
+    image_path: str,
+    db: Session,
+) -> VoiceProfileResponse:
+    """
+    Upload and process avatar image for a profile.
+
+    Args:
+        profile_id: Profile ID
+        image_path: Path to uploaded image file
+        db: Database session
+
+    Returns:
+        Updated profile
+    """
+    # Validate profile exists
+    profile = db.query(DBVoiceProfile).filter_by(id=profile_id).first()
+    if not profile:
+        raise ValueError(f"Profile {profile_id} not found")
+
+    # Validate image
+    is_valid, error_msg = validate_image(image_path)
+    if not is_valid:
+        raise ValueError(error_msg)
+
+    # Delete existing avatar if present
+    if profile.avatar_path:
+        old_avatar = Path(profile.avatar_path)
+        if old_avatar.exists():
+            old_avatar.unlink()
+
+    # Determine file extension from uploaded file
+    from PIL import Image
+    with Image.open(image_path) as img:
+        # Normalize JPEG variants (MPO is multi-picture format from some cameras)
+        img_format = img.format
+        if img_format in ('MPO', 'JPG'):
+            img_format = 'JPEG'
+        
+        ext_map = {
+            'PNG': '.png',
+            'JPEG': '.jpg',
+            'WEBP': '.webp'
+        }
+        ext = ext_map.get(img_format, '.png')
+
+    # Save processed image to profile directory
+    profile_dir = _get_profiles_dir() / profile_id
+    profile_dir.mkdir(parents=True, exist_ok=True)
+    output_path = profile_dir / f"avatar{ext}"
+
+    process_avatar(image_path, str(output_path))
+
+    # Update database
+    profile.avatar_path = str(output_path)
+    profile.updated_at = datetime.utcnow()
+
+    db.commit()
+    db.refresh(profile)
+
+    return VoiceProfileResponse.model_validate(profile)
+
+
+async def delete_avatar(
+    profile_id: str,
+    db: Session,
+) -> bool:
+    """
+    Delete avatar image for a profile.
+
+    Args:
+        profile_id: Profile ID
+        db: Database session
+
+    Returns:
+        True if deleted, False if not found or no avatar
+    """
+    profile = db.query(DBVoiceProfile).filter_by(id=profile_id).first()
+    if not profile or not profile.avatar_path:
+        return False
+
+    # Delete avatar file
+    avatar_path = Path(profile.avatar_path)
+    if avatar_path.exists():
+        avatar_path.unlink()
+
+    # Update database
+    profile.avatar_path = None
+    profile.updated_at = datetime.utcnow()
+
+    db.commit()
+
+    return True

backend/requirements-mlx.txt

@@ -0,0 +1,5 @@
+# MLX-specific dependencies (Apple Silicon only)
+# These should only be installed on aarch64-apple-darwin platforms
+
+mlx>=0.30.0
+mlx-audio>=0.3.1

backend/requirements.txt

@@ -21,3 +21,4 @@ numpy>=1.24.0
 
 # Utilities
 python-multipart>=0.0.6
+Pillow>=10.0.0

backend/stories.py

@@ -0,0 +1,972 @@
+"""
+Story management module.
+"""
+
+from typing import List, Optional
+from datetime import datetime
+import uuid
+import tempfile
+from pathlib import Path
+from sqlalchemy.orm import Session
+from sqlalchemy import func
+
+from .models import (
+    StoryCreate,
+    StoryResponse,
+    StoryDetailResponse,
+    StoryItemDetail,
+    StoryItemCreate,
+    StoryItemBatchUpdate,
+    StoryItemMove,
+    StoryItemTrim,
+    StoryItemSplit,
+)
+from .database import Story as DBStory, StoryItem as DBStoryItem, Generation as DBGeneration, VoiceProfile as DBVoiceProfile
+from .utils.audio import load_audio, save_audio
+import numpy as np
+
+
+async def create_story(
+    data: StoryCreate,
+    db: Session,
+) -> StoryResponse:
+    """
+    Create a new story.
+
+    Args:
+        data: Story creation data
+        db: Database session
+
+    Returns:
+        Created story
+    """
+    db_story = DBStory(
+        id=str(uuid.uuid4()),
+        name=data.name,
+        description=data.description,
+        created_at=datetime.utcnow(),
+        updated_at=datetime.utcnow(),
+    )
+
+    db.add(db_story)
+    db.commit()
+    db.refresh(db_story)
+
+    # Get item count
+    item_count = db.query(func.count(DBStoryItem.id)).filter(
+        DBStoryItem.story_id == db_story.id
+    ).scalar()
+
+    response = StoryResponse.model_validate(db_story)
+    response.item_count = item_count
+    return response
+
+
+async def list_stories(
+    db: Session,
+) -> List[StoryResponse]:
+    """
+    List all stories.
+
+    Args:
+        db: Database session
+
+    Returns:
+        List of stories with item counts
+    """
+    stories = db.query(DBStory).order_by(DBStory.updated_at.desc()).all()
+    
+    result = []
+    for story in stories:
+        item_count = db.query(func.count(DBStoryItem.id)).filter(
+            DBStoryItem.story_id == story.id
+        ).scalar()
+        
+        response = StoryResponse.model_validate(story)
+        response.item_count = item_count
+        result.append(response)
+    
+    return result
+
+
+async def get_story(
+    story_id: str,
+    db: Session,
+) -> Optional[StoryDetailResponse]:
+    """
+    Get a story with all its items.
+
+    Args:
+        story_id: Story ID
+        db: Database session
+
+    Returns:
+        Story with items or None if not found
+    """
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return None
+
+    # Get all items ordered by start_time_ms
+    items = db.query(
+        DBStoryItem,
+        DBGeneration,
+        DBVoiceProfile.name.label('profile_name')
+    ).join(
+        DBGeneration,
+        DBStoryItem.generation_id == DBGeneration.id
+    ).join(
+        DBVoiceProfile,
+        DBGeneration.profile_id == DBVoiceProfile.id
+    ).filter(
+        DBStoryItem.story_id == story_id
+    ).order_by(DBStoryItem.start_time_ms).all()
+
+    # Build item details
+    item_details = []
+    for item, generation, profile_name in items:
+        item_detail = StoryItemDetail(
+            id=item.id,
+            story_id=item.story_id,
+            generation_id=item.generation_id,
+            start_time_ms=item.start_time_ms,
+            track=item.track,
+            trim_start_ms=getattr(item, 'trim_start_ms', 0),
+            trim_end_ms=getattr(item, 'trim_end_ms', 0),
+            created_at=item.created_at,
+            profile_id=generation.profile_id,
+            profile_name=profile_name,
+            text=generation.text,
+            language=generation.language,
+            audio_path=generation.audio_path,
+            duration=generation.duration,
+            seed=generation.seed,
+            instruct=generation.instruct,
+            generation_created_at=generation.created_at,
+        )
+        item_details.append(item_detail)
+
+    response = StoryDetailResponse.model_validate(story)
+    response.items = item_details
+    return response
+
+
+async def update_story(
+    story_id: str,
+    data: StoryCreate,
+    db: Session,
+) -> Optional[StoryResponse]:
+    """
+    Update a story.
+
+    Args:
+        story_id: Story ID
+        data: Update data
+        db: Database session
+
+    Returns:
+        Updated story or None if not found
+    """
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return None
+
+    story.name = data.name
+    story.description = data.description
+    story.updated_at = datetime.utcnow()
+
+    db.commit()
+    db.refresh(story)
+
+    # Get item count
+    item_count = db.query(func.count(DBStoryItem.id)).filter(
+        DBStoryItem.story_id == story.id
+    ).scalar()
+
+    response = StoryResponse.model_validate(story)
+    response.item_count = item_count
+    return response
+
+
+async def delete_story(
+    story_id: str,
+    db: Session,
+) -> bool:
+    """
+    Delete a story and all its items.
+
+    Args:
+        story_id: Story ID
+        db: Database session
+
+    Returns:
+        True if deleted, False if not found
+    """
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return False
+
+    # Delete all items
+    db.query(DBStoryItem).filter_by(story_id=story_id).delete()
+
+    # Delete story
+    db.delete(story)
+    db.commit()
+
+    return True
+
+
+async def add_item_to_story(
+    story_id: str,
+    data: StoryItemCreate,
+    db: Session,
+) -> Optional[StoryItemDetail]:
+    """
+    Add a generation to a story.
+
+    Args:
+        story_id: Story ID
+        data: Item creation data
+        db: Database session
+
+    Returns:
+        Created item detail or None if story/generation not found
+    """
+    # Verify story exists
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return None
+
+    # Verify generation exists
+    generation = db.query(DBGeneration).filter_by(id=data.generation_id).first()
+    if not generation:
+        return None
+
+    # Check if generation is already in story
+    existing = db.query(DBStoryItem).filter_by(
+        story_id=story_id,
+        generation_id=data.generation_id
+    ).first()
+    if existing:
+        # Return existing item
+        profile = db.query(DBVoiceProfile).filter_by(id=generation.profile_id).first()
+        return StoryItemDetail(
+            id=existing.id,
+            story_id=existing.story_id,
+            generation_id=existing.generation_id,
+            start_time_ms=existing.start_time_ms,
+            track=existing.track,
+            trim_start_ms=getattr(existing, 'trim_start_ms', 0),
+            trim_end_ms=getattr(existing, 'trim_end_ms', 0),
+            created_at=existing.created_at,
+            profile_id=generation.profile_id,
+            profile_name=profile.name if profile else "Unknown",
+            text=generation.text,
+            language=generation.language,
+            audio_path=generation.audio_path,
+            duration=generation.duration,
+            seed=generation.seed,
+            instruct=generation.instruct,
+            generation_created_at=generation.created_at,
+        )
+
+    # 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
+        existing_items = db.query(
+            DBStoryItem,
+            DBGeneration
+        ).join(
+            DBGeneration,
+            DBStoryItem.generation_id == DBGeneration.id
+        ).filter(
+            DBStoryItem.story_id == story_id
+        ).all()
+        
+        if not existing_items:
+            # First item starts at 0
+            start_time_ms = 0
+        else:
+            max_end_time_ms = 0
+            for item, gen in existing_items:
+                item_end_ms = item.start_time_ms + int(gen.duration * 1000)
+                max_end_time_ms = max(max_end_time_ms, item_end_ms)
+            
+            # 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()),
+        story_id=story_id,
+        generation_id=data.generation_id,
+        start_time_ms=start_time_ms,
+        track=track,
+        created_at=datetime.utcnow(),
+    )
+
+    db.add(item)
+    
+    # Update story updated_at
+    story.updated_at = datetime.utcnow()
+    
+    db.commit()
+    db.refresh(item)
+
+    # Get profile name
+    profile = db.query(DBVoiceProfile).filter_by(id=generation.profile_id).first()
+
+    return StoryItemDetail(
+        id=item.id,
+        story_id=item.story_id,
+        generation_id=item.generation_id,
+        start_time_ms=item.start_time_ms,
+        track=item.track,
+        trim_start_ms=getattr(item, 'trim_start_ms', 0),
+        trim_end_ms=getattr(item, 'trim_end_ms', 0),
+        created_at=item.created_at,
+        profile_id=generation.profile_id,
+        profile_name=profile.name if profile else "Unknown",
+        text=generation.text,
+        language=generation.language,
+        audio_path=generation.audio_path,
+        duration=generation.duration,
+        seed=generation.seed,
+        instruct=generation.instruct,
+        generation_created_at=generation.created_at,
+    )
+
+
+async def move_story_item(
+    story_id: str,
+    item_id: str,
+    data: StoryItemMove,
+    db: Session,
+) -> Optional[StoryItemDetail]:
+    """
+    Move a story item (update position and/or track).
+
+    Args:
+        story_id: Story ID
+        item_id: Story item ID
+        data: New position and track data
+        db: Database session
+
+    Returns:
+        Updated item detail or None if not found
+    """
+    # Get the item
+    item = db.query(DBStoryItem).filter_by(
+        id=item_id,
+        story_id=story_id,
+    ).first()
+    if not item:
+        return None
+
+    # Get the generation
+    generation = db.query(DBGeneration).filter_by(id=item.generation_id).first()
+    if not generation:
+        return None
+
+    # Update position and track
+    item.start_time_ms = data.start_time_ms
+    item.track = data.track
+
+    # Update story updated_at
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if story:
+        story.updated_at = datetime.utcnow()
+
+    db.commit()
+    db.refresh(item)
+
+    # Get profile name
+    profile = db.query(DBVoiceProfile).filter_by(id=generation.profile_id).first()
+
+    return StoryItemDetail(
+        id=item.id,
+        story_id=item.story_id,
+        generation_id=item.generation_id,
+        start_time_ms=item.start_time_ms,
+        track=item.track,
+        trim_start_ms=getattr(item, 'trim_start_ms', 0),
+        trim_end_ms=getattr(item, 'trim_end_ms', 0),
+        created_at=item.created_at,
+        profile_id=generation.profile_id,
+        profile_name=profile.name if profile else "Unknown",
+        text=generation.text,
+        language=generation.language,
+        audio_path=generation.audio_path,
+        duration=generation.duration,
+        seed=generation.seed,
+        instruct=generation.instruct,
+        generation_created_at=generation.created_at,
+    )
+
+
+async def remove_item_from_story(
+    story_id: str,
+    item_id: str,
+    db: Session,
+) -> bool:
+    """
+    Remove a story item from a story.
+
+    Args:
+        story_id: Story ID
+        item_id: Story item ID to remove
+        db: Database session
+
+    Returns:
+        True if removed, False if not found
+    """
+    item = db.query(DBStoryItem).filter_by(
+        id=item_id,
+        story_id=story_id,
+    ).first()
+    if not item:
+        return False
+
+    # Delete item
+    db.delete(item)
+
+    # Update story updated_at
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if story:
+        story.updated_at = datetime.utcnow()
+
+    db.commit()
+    return True
+
+
+async def trim_story_item(
+    story_id: str,
+    item_id: str,
+    data: StoryItemTrim,
+    db: Session,
+) -> Optional[StoryItemDetail]:
+    """
+    Trim a story item (update trim_start_ms and trim_end_ms).
+
+    Args:
+        story_id: Story ID
+        item_id: Story item ID
+        data: Trim data (trim_start_ms, trim_end_ms)
+        db: Database session
+
+    Returns:
+        Updated item detail or None if not found
+    """
+    # Get the item
+    item = db.query(DBStoryItem).filter_by(
+        id=item_id,
+        story_id=story_id,
+    ).first()
+    if not item:
+        return None
+
+    # Get the generation
+    generation = db.query(DBGeneration).filter_by(id=item.generation_id).first()
+    if not generation:
+        return None
+
+    # Validate trim values don't exceed duration
+    max_duration_ms = int(generation.duration * 1000)
+    if data.trim_start_ms + data.trim_end_ms >= max_duration_ms:
+        return None  # Invalid trim - would result in zero or negative duration
+
+    # Update trim values
+    item.trim_start_ms = data.trim_start_ms
+    item.trim_end_ms = data.trim_end_ms
+
+    # Update story updated_at
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if story:
+        story.updated_at = datetime.utcnow()
+
+    db.commit()
+    db.refresh(item)
+
+    # Get profile name
+    profile = db.query(DBVoiceProfile).filter_by(id=generation.profile_id).first()
+
+    return StoryItemDetail(
+        id=item.id,
+        story_id=item.story_id,
+        generation_id=item.generation_id,
+        start_time_ms=item.start_time_ms,
+        track=item.track,
+        trim_start_ms=item.trim_start_ms,
+        trim_end_ms=item.trim_end_ms,
+        created_at=item.created_at,
+        profile_id=generation.profile_id,
+        profile_name=profile.name if profile else "Unknown",
+        text=generation.text,
+        language=generation.language,
+        audio_path=generation.audio_path,
+        duration=generation.duration,
+        seed=generation.seed,
+        instruct=generation.instruct,
+        generation_created_at=generation.created_at,
+    )
+
+
+async def split_story_item(
+    story_id: str,
+    item_id: str,
+    data: StoryItemSplit,
+    db: Session,
+) -> Optional[List[StoryItemDetail]]:
+    """
+    Split a story item at a given time, creating two clips.
+
+    Args:
+        story_id: Story ID
+        item_id: Story item ID to split
+        data: Split data (split_time_ms - time within clip to split at)
+        db: Database session
+
+    Returns:
+        List of two updated item details (original and new) or None if not found/invalid
+    """
+    # Get the item
+    item = db.query(DBStoryItem).filter_by(
+        id=item_id,
+        story_id=story_id,
+    ).first()
+    if not item:
+        return None
+
+    # Get the generation
+    generation = db.query(DBGeneration).filter_by(id=item.generation_id).first()
+    if not generation:
+        return None
+
+    # Calculate effective duration and validate split point
+    current_trim_start = getattr(item, 'trim_start_ms', 0)
+    current_trim_end = getattr(item, 'trim_end_ms', 0)
+    original_duration_ms = int(generation.duration * 1000)
+    effective_duration_ms = original_duration_ms - current_trim_start - current_trim_end
+
+    # Validate split_time_ms is within the effective duration
+    if data.split_time_ms <= 0 or data.split_time_ms >= effective_duration_ms:
+        return None  # Invalid split point
+
+    # Calculate the absolute time in the original audio where we're splitting
+    absolute_split_ms = current_trim_start + data.split_time_ms
+
+    # Update original clip: trim from the end
+    item.trim_end_ms = original_duration_ms - absolute_split_ms
+
+    # Create new clip: starts after the split, trimmed from the start
+    new_item = DBStoryItem(
+        id=str(uuid.uuid4()),
+        story_id=story_id,
+        generation_id=item.generation_id,  # Same generation, different trim
+        start_time_ms=item.start_time_ms + data.split_time_ms,
+        track=item.track,
+        trim_start_ms=absolute_split_ms,
+        trim_end_ms=current_trim_end,
+        created_at=datetime.utcnow(),
+    )
+
+    db.add(new_item)
+
+    # Update story updated_at
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if story:
+        story.updated_at = datetime.utcnow()
+
+    db.commit()
+    db.refresh(item)
+    db.refresh(new_item)
+
+    # Get profile name
+    profile = db.query(DBVoiceProfile).filter_by(id=generation.profile_id).first()
+    profile_name = profile.name if profile else "Unknown"
+
+    # Build response items
+    original_item_detail = StoryItemDetail(
+        id=item.id,
+        story_id=item.story_id,
+        generation_id=item.generation_id,
+        start_time_ms=item.start_time_ms,
+        track=item.track,
+        trim_start_ms=item.trim_start_ms,
+        trim_end_ms=item.trim_end_ms,
+        created_at=item.created_at,
+        profile_id=generation.profile_id,
+        profile_name=profile_name,
+        text=generation.text,
+        language=generation.language,
+        audio_path=generation.audio_path,
+        duration=generation.duration,
+        seed=generation.seed,
+        instruct=generation.instruct,
+        generation_created_at=generation.created_at,
+    )
+
+    new_item_detail = StoryItemDetail(
+        id=new_item.id,
+        story_id=new_item.story_id,
+        generation_id=new_item.generation_id,
+        start_time_ms=new_item.start_time_ms,
+        track=new_item.track,
+        trim_start_ms=new_item.trim_start_ms,
+        trim_end_ms=new_item.trim_end_ms,
+        created_at=new_item.created_at,
+        profile_id=generation.profile_id,
+        profile_name=profile_name,
+        text=generation.text,
+        language=generation.language,
+        audio_path=generation.audio_path,
+        duration=generation.duration,
+        seed=generation.seed,
+        instruct=generation.instruct,
+        generation_created_at=generation.created_at,
+    )
+
+    return [original_item_detail, new_item_detail]
+
+
+async def duplicate_story_item(
+    story_id: str,
+    item_id: str,
+    db: Session,
+) -> Optional[StoryItemDetail]:
+    """
+    Duplicate a story item, creating a copy with all properties.
+
+    Args:
+        story_id: Story ID
+        item_id: Story item ID to duplicate
+        db: Database session
+
+    Returns:
+        New item detail or None if not found
+    """
+    # Get the original item
+    original_item = db.query(DBStoryItem).filter_by(
+        id=item_id,
+        story_id=story_id,
+    ).first()
+    if not original_item:
+        return None
+
+    # Get the generation
+    generation = db.query(DBGeneration).filter_by(id=original_item.generation_id).first()
+    if not generation:
+        return None
+
+    # Calculate effective duration
+    current_trim_start = getattr(original_item, 'trim_start_ms', 0)
+    current_trim_end = getattr(original_item, 'trim_end_ms', 0)
+    original_duration_ms = int(generation.duration * 1000)
+    effective_duration_ms = original_duration_ms - current_trim_start - current_trim_end
+
+    # Create duplicate item - place it right after the original
+    new_item = DBStoryItem(
+        id=str(uuid.uuid4()),
+        story_id=story_id,
+        generation_id=original_item.generation_id,  # Same generation as original
+        start_time_ms=original_item.start_time_ms + effective_duration_ms + 200,  # 200ms gap
+        track=original_item.track,
+        trim_start_ms=current_trim_start,
+        trim_end_ms=current_trim_end,
+        created_at=datetime.utcnow(),
+    )
+
+    db.add(new_item)
+
+    # Update story updated_at
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if story:
+        story.updated_at = datetime.utcnow()
+
+    db.commit()
+    db.refresh(new_item)
+
+    # Get profile name
+    profile = db.query(DBVoiceProfile).filter_by(id=generation.profile_id).first()
+
+    return StoryItemDetail(
+        id=new_item.id,
+        story_id=new_item.story_id,
+        generation_id=new_item.generation_id,
+        start_time_ms=new_item.start_time_ms,
+        track=new_item.track,
+        trim_start_ms=new_item.trim_start_ms,
+        trim_end_ms=new_item.trim_end_ms,
+        created_at=new_item.created_at,
+        profile_id=generation.profile_id,
+        profile_name=profile.name if profile else "Unknown",
+        text=generation.text,
+        language=generation.language,
+        audio_path=generation.audio_path,
+        duration=generation.duration,
+        seed=generation.seed,
+        instruct=generation.instruct,
+        generation_created_at=generation.created_at,
+    )
+
+
+async def update_story_item_times(
+    story_id: str,
+    data: StoryItemBatchUpdate,
+    db: Session,
+) -> bool:
+    """
+    Update story item timecodes.
+
+    Args:
+        story_id: Story ID
+        data: Batch update data with timecodes
+        db: Database session
+
+    Returns:
+        True if updated, False if story not found or invalid
+    """
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return False
+
+    # Get all items for this story
+    items = db.query(DBStoryItem).filter_by(story_id=story_id).all()
+    item_map = {item.generation_id: item for item in items}
+
+    # Verify all generation IDs belong to this story and update timecodes
+    for update in data.updates:
+        if update.generation_id not in item_map:
+            return False
+        item_map[update.generation_id].start_time_ms = update.start_time_ms
+
+    # Update story updated_at
+    story.updated_at = datetime.utcnow()
+
+    db.commit()
+    return True
+
+
+async def reorder_story_items(
+    story_id: str,
+    generation_ids: List[str],
+    db: Session,
+    gap_ms: int = 200,
+) -> Optional[List[StoryItemDetail]]:
+    """
+    Reorder story items and recalculate timecodes.
+
+    Args:
+        story_id: Story ID
+        generation_ids: List of generation IDs in the desired order
+        db: Database session
+        gap_ms: Gap in milliseconds between items (default 200ms)
+
+    Returns:
+        Updated list of story items with new timecodes, or None if invalid
+    """
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return None
+
+    # Get all items for this story with their generation data
+    items_with_gen = db.query(
+        DBStoryItem,
+        DBGeneration,
+        DBVoiceProfile.name.label('profile_name')
+    ).join(
+        DBGeneration,
+        DBStoryItem.generation_id == DBGeneration.id
+    ).join(
+        DBVoiceProfile,
+        DBGeneration.profile_id == DBVoiceProfile.id
+    ).filter(
+        DBStoryItem.story_id == story_id
+    ).all()
+
+    # Create maps for quick lookup
+    item_map = {item.generation_id: (item, gen, profile_name) for item, gen, profile_name in items_with_gen}
+
+    # Verify all generation IDs belong to this story
+    if set(generation_ids) != set(item_map.keys()):
+        return None
+
+    # Recalculate timecodes based on new order
+    current_time_ms = 0
+    updated_items = []
+
+    for gen_id in generation_ids:
+        item, generation, profile_name = item_map[gen_id]
+        
+        # Update the item's start time
+        item.start_time_ms = current_time_ms
+        
+        # Calculate the duration in ms
+        duration_ms = int(generation.duration * 1000)
+        
+        # Move to next position (current end + gap)
+        current_time_ms += duration_ms + gap_ms
+
+        # Build the response item
+        updated_items.append(StoryItemDetail(
+            id=item.id,
+            story_id=item.story_id,
+            generation_id=item.generation_id,
+            start_time_ms=item.start_time_ms,
+            track=item.track,
+            trim_start_ms=getattr(item, 'trim_start_ms', 0),
+            trim_end_ms=getattr(item, 'trim_end_ms', 0),
+            created_at=item.created_at,
+            profile_id=generation.profile_id,
+            profile_name=profile_name,
+            text=generation.text,
+            language=generation.language,
+            audio_path=generation.audio_path,
+            duration=generation.duration,
+            seed=generation.seed,
+            instruct=generation.instruct,
+            generation_created_at=generation.created_at,
+        ))
+
+    # Update story updated_at
+    story.updated_at = datetime.utcnow()
+
+    db.commit()
+    return updated_items
+
+
+async def export_story_audio(
+    story_id: str,
+    db: Session,
+) -> Optional[bytes]:
+    """
+    Export story as single mixed audio file with timecode-based mixing.
+
+    Args:
+        story_id: Story ID
+        db: Database session
+
+    Returns:
+        Audio file bytes or None if story not found
+    """
+    story = db.query(DBStory).filter_by(id=story_id).first()
+    if not story:
+        return None
+
+    # Get all items ordered by start_time_ms
+    items = db.query(
+        DBStoryItem,
+        DBGeneration
+    ).join(
+        DBGeneration,
+        DBStoryItem.generation_id == DBGeneration.id
+    ).filter(
+        DBStoryItem.story_id == story_id
+    ).order_by(DBStoryItem.start_time_ms).all()
+
+    if not items:
+        return None
+
+    # Load all audio files and calculate total duration
+    audio_data = []
+    sample_rate = 24000  # Default sample rate
+
+    for item, generation in items:
+        audio_path = Path(generation.audio_path)
+        if not audio_path.exists():
+            continue
+
+        try:
+            audio, sr = load_audio(str(audio_path), sample_rate=sample_rate)
+            sample_rate = sr  # Use actual sample rate from first file
+            
+            # Get trim values
+            trim_start_ms = getattr(item, 'trim_start_ms', 0)
+            trim_end_ms = getattr(item, 'trim_end_ms', 0)
+            
+            # Calculate effective duration
+            original_duration_ms = int(generation.duration * 1000)
+            effective_duration_ms = original_duration_ms - trim_start_ms - trim_end_ms
+            
+            # Slice audio based on trim values
+            trim_start_sample = int((trim_start_ms / 1000.0) * sample_rate)
+            trim_end_sample = int((trim_end_ms / 1000.0) * sample_rate)
+            
+            # Extract the trimmed portion
+            if trim_end_ms > 0:
+                trimmed_audio = audio[trim_start_sample:-trim_end_sample] if trim_end_sample > 0 else audio[trim_start_sample:]
+            else:
+                trimmed_audio = audio[trim_start_sample:]
+            
+            # Store audio with its timecode info
+            start_time_ms = item.start_time_ms
+            
+            audio_data.append({
+                'audio': trimmed_audio,
+                'start_time_ms': start_time_ms,
+                'duration_ms': effective_duration_ms,
+            })
+        except Exception:
+            # Skip files that can't be loaded
+            continue
+
+    if not audio_data:
+        return None
+
+    # Calculate total duration: max(start_time_ms + duration_ms)
+    max_end_time_ms = max(
+        (data['start_time_ms'] + data['duration_ms'] for data in audio_data),
+        default=0
+    )
+    
+    # Convert to samples
+    total_samples = int((max_end_time_ms / 1000.0) * sample_rate)
+    
+    # Create output buffer initialized to zeros
+    final_audio = np.zeros(total_samples, dtype=np.float32)
+
+    # Mix each audio segment at its timecode position
+    for data in audio_data:
+        audio = data['audio']
+        start_time_ms = data['start_time_ms']
+        
+        # Calculate start sample index
+        start_sample = int((start_time_ms / 1000.0) * sample_rate)
+        
+        # Ensure we don't exceed buffer bounds
+        audio_length = len(audio)
+        end_sample = min(start_sample + audio_length, total_samples)
+        
+        if start_sample < total_samples:
+            # Trim audio if it extends beyond buffer
+            audio_to_mix = audio[:end_sample - start_sample]
+            
+            # Mix: add audio to existing buffer (overlapping audio will sum)
+            # Normalize to prevent clipping (simple approach: divide by max)
+            final_audio[start_sample:end_sample] += audio_to_mix
+
+    # Normalize to prevent clipping
+    max_val = np.abs(final_audio).max()
+    if max_val > 1.0:
+        final_audio = final_audio / max_val
+
+    # Save to temporary file
+    with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp:
+        tmp_path = tmp.name
+
+    try:
+        save_audio(final_audio, tmp_path, sample_rate)
+
+        # Read file bytes
+        with open(tmp_path, 'rb') as f:
+            audio_bytes = f.read()
+
+        return audio_bytes
+    finally:
+        # Clean up temp file
+        Path(tmp_path).unlink(missing_ok=True)

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_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_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/transcribe.py

@@ -1,274 +1,22 @@
 """
-Whisper ASR module for transcription.
+STT (Speech-to-Text) module - delegates to backend abstraction layer.
 """
 
-from typing import Optional, List, Dict
-import asyncio
-import torch
-import numpy as np
-from pathlib import Path
-from .utils.progress import get_progress_manager
-from .utils.hf_progress import HFProgressTracker, create_hf_progress_callback
-from .utils.tasks import get_task_manager
+from typing import Optional
+from .backends import get_stt_backend, STTBackend
 
 
-class WhisperModel:
-    """Manages Whisper model loading and transcription."""
+def get_whisper_model() -> STTBackend:
+    """
+    Get STT backend instance (MLX or PyTorch based on platform).
     
-    def __init__(self, model_size: str = "base"):
-        self.model = None
-        self.processor = None
-        self.model_size = model_size
-        self.device = self._get_device()
-    
-    def _get_device(self) -> str:
-        """Get the best available device."""
-        if torch.cuda.is_available():
-            return "cuda"
-        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
-            # MPS support for Whisper
-            return "cpu"  # Use CPU for stability
-        return "cpu"
-    
-    def is_loaded(self) -> bool:
-        """Check if model is loaded."""
-        return self.model is not None
-    
-    def load_model(self, model_size: Optional[str] = None):
-        """
-        Lazy load the Whisper model.
-        
-        Args:
-            model_size: Model size (tiny, base, small, medium, large)
-        """
-        if model_size is None:
-            model_size = self.model_size
-        
-        if self.model is not None and self.model_size == model_size:
-            return
-        
-        try:
-            from transformers import WhisperProcessor, WhisperForConditionalGeneration
-            
-            model_name = f"openai/whisper-{model_size}"
-            
-            # Set up progress tracking
-            progress_manager = get_progress_manager()
-            progress_model_name = f"whisper-{model_size}"
-            
-            # Start tracking download task
-            task_manager = get_task_manager()
-            task_manager.start_download(progress_model_name)
-            
-            print(f"Loading Whisper model {model_size} on {self.device}...")
-            
-            # Initialize progress state to show download has started
-            progress_manager.update_progress(
-                model_name=progress_model_name,
-                current=0,
-                total=1,  # Set to 1 initially, will be updated by callback
-                filename="",
-                status="downloading",
-            )
-            
-            # Set up progress callback
-            progress_callback = create_hf_progress_callback(progress_model_name, progress_manager)
-            tracker = HFProgressTracker(progress_callback)
-            
-            # Use progress tracker during download
-            with tracker.patch_download():
-                self.processor = WhisperProcessor.from_pretrained(model_name)
-                self.model = WhisperForConditionalGeneration.from_pretrained(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:
-            print(f"Error loading Whisper model: {e}")
-            progress_manager = get_progress_manager()
-            task_manager = get_task_manager()
-            progress_model_name = f"whisper-{model_size}"
-            progress_manager.mark_error(progress_model_name, str(e))
-            task_manager.error_download(progress_model_name, str(e))
-            raise
-    
-    async def load_model_async(self, model_size: Optional[str] = None):
-        """
-        Async version of load_model that runs in thread pool.
-        
-        This prevents blocking the event loop during model loading.
-        """
-        if model_size is None:
-            model_size = self.model_size
-            
-        # If already loaded with correct size, return immediately
-        if self.model is not None and self.model_size == model_size:
-            return
-        
-        # Run the blocking load operation in a thread pool
-        await asyncio.to_thread(self.load_model, model_size)
-    
-    def unload_model(self):
-        """Unload the model to free memory."""
-        if self.model is not None:
-            del self.model
-            del self.processor
-            self.model = None
-            self.processor = None
-            
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
-            
-            print("Whisper model unloaded")
-    
-    async def transcribe(
-        self,
-        audio_path: str,
-        language: Optional[str] = None,
-    ) -> str:
-        """
-        Transcribe audio to text.
-        
-        Args:
-            audio_path: Path to audio file
-            language: Optional language hint (en or zh)
-            
-        Returns:
-            Transcribed text
-        """
-        await self.load_model_async()
-        
-        from .utils.audio import load_audio
-        
-        def _transcribe_sync():
-            """Run synchronous transcription in thread pool."""
-            # Load audio
-            audio, sr = load_audio(audio_path, sample_rate=16000)
-            
-            # Process audio
-            inputs = self.processor(
-                audio,
-                sampling_rate=16000,
-                return_tensors="pt",
-            )
-            inputs = inputs.to(self.device)
-            
-            # Set language if provided
-            forced_decoder_ids = None
-            if language:
-                lang_code = "en" if language == "en" else "zh"
-                forced_decoder_ids = self.processor.get_decoder_prompt_ids(
-                    language=lang_code,
-                    task="transcribe",
-                )
-            
-            # Generate transcription
-            with torch.no_grad():
-                predicted_ids = self.model.generate(
-                    inputs["input_features"],
-                    forced_decoder_ids=forced_decoder_ids,
-                )
-            
-            # Decode
-            transcription = self.processor.batch_decode(
-                predicted_ids,
-                skip_special_tokens=True,
-            )[0]
-            
-            return transcription.strip()
-        
-        # Run blocking transcription in thread pool
-        return await asyncio.to_thread(_transcribe_sync)
-    
-    async def transcribe_with_timestamps(
-        self,
-        audio_path: str,
-        language: Optional[str] = None,
-    ) -> List[Dict[str, any]]:
-        """
-        Transcribe audio with word-level timestamps.
-        
-        Args:
-            audio_path: Path to audio file
-            language: Optional language hint
-            
-        Returns:
-            List of word segments with timestamps
-        """
-        await self.load_model_async()
-        
-        from .utils.audio import load_audio
-        
-        def _transcribe_timestamps_sync():
-            """Run synchronous transcription with timestamps in thread pool."""
-            # Load audio
-            audio, sr = load_audio(audio_path, sample_rate=16000)
-            
-            # Process audio
-            inputs = self.processor(
-                audio,
-                sampling_rate=16000,
-                return_tensors="pt",
-            )
-            inputs = inputs.to(self.device)
-            
-            # Set language if provided
-            forced_decoder_ids = None
-            if language:
-                lang_code = "en" if language == "en" else "zh"
-                forced_decoder_ids = self.processor.get_decoder_prompt_ids(
-                    language=lang_code,
-                    task="transcribe",
-                )
-            
-            # Generate with timestamps
-            with torch.no_grad():
-                predicted_ids = self.model.generate(
-                    inputs["input_features"],
-                    forced_decoder_ids=forced_decoder_ids,
-                    return_timestamps=True,
-                )
-            
-            # Parse timestamps (simplified - would need more robust parsing)
-            # For now, return basic transcription
-            # TODO: Implement proper timestamp parsing
-            transcription = self.processor.batch_decode(
-                predicted_ids,
-                skip_special_tokens=True,
-            )[0]
-            
-            return [
-                {
-                    "text": transcription,
-                    "start": 0.0,
-                    "end": len(audio) / sr,
-                }
-            ]
-        
-        # Run blocking transcription in thread pool
-        return await asyncio.to_thread(_transcribe_timestamps_sync)
-
-
-# Global model instance
-_whisper_model: Optional[WhisperModel] = None
-
-
-def get_whisper_model() -> WhisperModel:
-    """Get or create Whisper model instance."""
-    global _whisper_model
-    if _whisper_model is None:
-        _whisper_model = WhisperModel()
-    return _whisper_model
+    Returns:
+        STT backend instance
+    """
+    return get_stt_backend()
 
 
 def unload_whisper_model():
     """Unload Whisper model to free memory."""
-    global _whisper_model
-    if _whisper_model is not None:
-        _whisper_model.unload_model()
+    backend = get_stt_backend()
+    backend.unload_model()

backend/tts.py

@@ -1,372 +1,37 @@
 """
-TTS inference module using Qwen3-TTS.
+TTS inference module - delegates to backend abstraction layer.
 """
 
-from typing import Optional, List, Tuple
-import asyncio
-import torch
+from typing import Optional
 import numpy as np
 import io
 import soundfile as sf
-from pathlib import Path
 
-from .utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
-from .utils.audio import normalize_audio
-from .utils.progress import get_progress_manager
-from .utils.hf_progress import HFProgressTracker, create_hf_progress_callback
-from .utils.tasks import get_task_manager
-from . import config
+from .backends import get_tts_backend, TTSBackend
 
 
-class TTSModel:
-    """Manages Qwen3-TTS model loading and inference."""
+def get_tts_model() -> TTSBackend:
+    """
+    Get TTS backend instance (MLX or PyTorch based on platform).
     
-    def __init__(self, model_size: str = "1.7B"):
-        self.model = None
-        self.model_size = model_size
-        self.device = self._get_device()
-        self._current_model_size = None
-    
-    def _get_device(self) -> str:
-        """Get the best available device."""
-        if torch.cuda.is_available():
-            return "cuda"
-        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
-            # MPS can have issues, use CPU for stability
-            return "cpu"
-        return "cpu"
-    
-    def is_loaded(self) -> bool:
-        """Check if model is loaded."""
-        return self.model is not None
-    
-    def _get_model_path(self, model_size: str) -> str:
-        """
-        Get the model path, downloading from HuggingFace Hub if needed.
-        
-        Args:
-            model_size: Model size (1.7B or 0.6B)
-            
-        Returns:
-            Path to model (either local or HuggingFace Hub ID)
-        """
-        # HuggingFace Hub model IDs
-        hf_model_map = {
-            "1.7B": "Qwen/Qwen3-TTS-12Hz-1.7B-Base",
-            "0.6B": "Qwen/Qwen3-TTS-12Hz-0.6B-Base",
-        }
-        
-        # Local directory names (for backwards compatibility)
-        local_model_map = {
-            "1.7B": "Qwen--Qwen3-TTS-12Hz-1.7B-Base",
-            "0.6B": "Qwen--Qwen3-TTS-12Hz-0.6B-Base",
-        }
-        
-        if model_size not in hf_model_map:
-            raise ValueError(f"Unknown model size: {model_size}")
-        
-        # Check if model exists locally (backwards compatibility)
-        local_path = config.get_models_dir() / local_model_map[model_size]
-        if local_path.exists():
-            print(f"Found local model at {local_path}")
-            return str(local_path)
-        
-        # Use HuggingFace Hub model ID (will auto-download)
-        hf_model_id = hf_model_map[model_size]
-        print(f"Will download model from HuggingFace Hub: {hf_model_id}")
-        
-        return hf_model_id
-    
-    def load_model(self, model_size: Optional[str] = None):
-        """
-        Lazy load the TTS model with automatic downloading from HuggingFace Hub.
-        
-        The model will be automatically downloaded on first use and cached locally.
-        This works similar to how Whisper models are loaded.
-        
-        Args:
-            model_size: Model size to load (1.7B or 0.6B)
-        """
-        if model_size is None:
-            model_size = self.model_size
-            
-        # If already loaded with correct size, return
-        if self.model is not None and self._current_model_size == model_size:
-            return
-        
-        # Unload existing model if different size requested
-        if self.model is not None and self._current_model_size != model_size:
-            self.unload_model()
-        
-        try:
-            from qwen_tts import Qwen3TTSModel
-            
-            # Get model path (local or HuggingFace Hub ID)
-            model_path = self._get_model_path(model_size)
-            
-            # Set up progress tracking
-            progress_manager = get_progress_manager()
-            model_name = f"qwen-tts-{model_size}"
-            
-            # Check if model is being downloaded from HuggingFace Hub
-            if model_path.startswith("Qwen/"):
-                print(f"Loading TTS model {model_size} on {self.device}...")
-                
-                # Start tracking download task
-                task_manager = get_task_manager()
-                task_manager.start_download(model_name)
-                
-                # Initialize progress state to show download has started
-                progress_manager.update_progress(
-                    model_name=model_name,
-                    current=0,
-                    total=1,  # Set to 1 initially, will be updated by callback
-                    filename="",
-                    status="downloading",
-                )
-                
-                # Set up progress callback
-                progress_callback = create_hf_progress_callback(model_name, progress_manager)
-                tracker = HFProgressTracker(progress_callback)
-                
-                # Use progress tracker during download
-                with tracker.patch_download():
-                    # Load the model - downloads will happen automatically with progress tracking
-                    self.model = Qwen3TTSModel.from_pretrained(
-                        model_path,
-                        device_map=self.device,
-                        torch_dtype=torch.float32 if self.device == "cpu" else torch.bfloat16,
-                    )
-                
-                # Mark as complete
-                progress_manager.mark_complete(model_name)
-                task_manager.complete_download(model_name)
-            else:
-                # Local model, no download needed
-                print(f"Loading TTS model {model_size} on {self.device}...")
-                self.model = Qwen3TTSModel.from_pretrained(
-                    model_path,
-                    device_map=self.device,
-                    torch_dtype=torch.float32 if self.device == "cpu" else torch.bfloat16,
-                )
-            
-            self._current_model_size = model_size
-            self.model_size = model_size
-            
-            print(f"TTS model {model_size} loaded successfully")
-            
-        except ImportError as e:
-            print(f"Error: qwen_tts package not found. Install with: pip install git+https://github.com/QwenLM/Qwen3-TTS.git")
-            progress_manager = get_progress_manager()
-            task_manager = get_task_manager()
-            model_name = f"qwen-tts-{model_size}"
-            progress_manager.mark_error(model_name, str(e))
-            task_manager.error_download(model_name, str(e))
-            raise
-        except Exception as e:
-            print(f"Error loading TTS model: {e}")
-            print(f"Tip: The model will be automatically downloaded from HuggingFace Hub on first use.")
-            progress_manager = get_progress_manager()
-            task_manager = get_task_manager()
-            model_name = f"qwen-tts-{model_size}"
-            progress_manager.mark_error(model_name, str(e))
-            task_manager.error_download(model_name, str(e))
-            raise
-    
-    async def load_model_async(self, model_size: Optional[str] = None):
-        """
-        Async version of load_model that runs in thread pool.
-        
-        This prevents blocking the event loop during model loading.
-        """
-        if model_size is None:
-            model_size = self.model_size
-            
-        # If already loaded with correct size, return immediately
-        if self.model is not None and self._current_model_size == model_size:
-            return
-        
-        # Run the blocking load operation in a thread pool
-        await asyncio.to_thread(self.load_model, model_size)
-    
-    def unload_model(self):
-        """Unload the model to free memory."""
-        if self.model is not None:
-            del self.model
-            self.model = None
-            self._current_model_size = None
-            
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
-            
-            print("TTS model 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.
-        
-        Args:
-            audio_path: Path to reference audio file
-            reference_text: Transcript of reference audio
-            use_cache: Whether to use cached prompt if available
-            
-        Returns:
-            Tuple of (voice_prompt_dict, was_cached)
-        """
-        await self.load_model_async()
-        
-        # Check cache if enabled
-        if use_cache:
-            cache_key = get_cache_key(audio_path, reference_text)
-            cached_prompt = get_cached_voice_prompt(cache_key)
-            if cached_prompt is not None:
-                return cached_prompt, True
-        
-        def _create_prompt_sync():
-            """Run synchronous voice prompt creation in thread pool."""
-            return self.model.create_voice_clone_prompt(
-                ref_audio=str(audio_path),
-                ref_text=reference_text,
-                x_vector_only_mode=False,
-            )
-        
-        # Run blocking operation in thread pool
-        voice_prompt_items = await asyncio.to_thread(_create_prompt_sync)
-        
-        # Cache if enabled
-        if use_cache:
-            cache_voice_prompt(cache_key, voice_prompt_items)
-        
-        return voice_prompt_items, False
-    
-    async def combine_voice_prompts(
-        self,
-        audio_paths: List[str],
-        reference_texts: List[str],
-    ) -> Tuple[np.ndarray, str]:
-        """
-        Combine multiple reference samples for better quality.
-        
-        Args:
-            audio_paths: List of audio file paths
-            reference_texts: List of reference texts
-            
-        Returns:
-            Tuple of (combined_audio, combined_text)
-        """
-        from .utils.audio import load_audio
-        
-        combined_audio = []
-        
-        for audio_path in audio_paths:
-            audio, sr = load_audio(audio_path)
-            audio = normalize_audio(audio)
-            combined_audio.append(audio)
-        
-        # Concatenate audio
-        mixed = np.concatenate(combined_audio)
-        mixed = normalize_audio(mixed)
-        
-        # Combine texts
-        combined_text = " ".join(reference_texts)
-        
-        return mixed, combined_text
-    
-    async def 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 voice prompt.
-
-        Args:
-            text: Text to synthesize
-            voice_prompt: Voice prompt dictionary from create_voice_prompt
-            language: Language code (en or zh)
-            seed: Random seed for reproducibility
-            instruct: Natural language instruction for speech delivery control
-
-        Returns:
-            Tuple of (audio_array, sample_rate)
-        """
-        # Load model (already handles async via to_thread if needed)
-        await self.load_model_async()
-
-        def _generate_sync():
-            """Run synchronous generation in thread pool."""
-            # Set seed if provided
-            if seed is not None:
-                torch.manual_seed(seed)
-                if torch.cuda.is_available():
-                    torch.cuda.manual_seed(seed)
-
-            # Generate audio - this is the blocking operation
-            wavs, sample_rate = self.model.generate_voice_clone(
-                text=text,
-                voice_clone_prompt=voice_prompt,
-                instruct=instruct,
-            )
-            return wavs[0], sample_rate
-
-        # Run blocking inference in thread pool to avoid blocking event loop
-        audio, sample_rate = await asyncio.to_thread(_generate_sync)
-
-        return audio, sample_rate
-    
-    async def generate_from_reference(
-        self,
-        text: str,
-        audio_path: str,
-        reference_text: str,
-        language: str = "en",
-        seed: Optional[int] = None,
-    ) -> Tuple[np.ndarray, int]:
-        """
-        Generate audio directly from reference (convenience method).
-        
-        Args:
-            text: Text to synthesize
-            audio_path: Path to reference audio
-            reference_text: Transcript of reference audio
-            language: Language code
-            seed: Random seed
-            
-        Returns:
-            Tuple of (audio_array, sample_rate)
-        """
-        # Create voice prompt (with caching)
-        voice_prompt, _ = await self.create_voice_prompt(audio_path, reference_text)
-        
-        # Generate
-        return await self.generate(text, voice_prompt, language, seed)
-
-
-# Global model instance
-_tts_model: Optional[TTSModel] = None
-
-
-def get_tts_model() -> TTSModel:
-    """Get or create TTS model instance."""
-    global _tts_model
-    if _tts_model is None:
-        _tts_model = TTSModel()
-    return _tts_model
+    Returns:
+        TTS backend instance
+    """
+    return get_tts_backend()
 
 
 def unload_tts_model():
     """Unload TTS model to free memory."""
-    global _tts_model
-    if _tts_model is not None:
-        _tts_model.unload_model()
+    backend = get_tts_backend()
+    backend.unload_model()
+
+
+def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes:
+    """Convert audio array to WAV bytes."""
+    buffer = io.BytesIO()
+    sf.write(buffer, audio, sample_rate, format="WAV")
+    buffer.seek(0)
+    return buffer.read()
 
 
 def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes:

backend/utils/cache.py

@@ -5,7 +5,7 @@ Voice prompt caching utilities.
 import hashlib
 import torch
 from pathlib import Path
-from typing import Optional
+from typing import Optional, Union, Dict, Any
 
 from .. import config
 
@@ -15,8 +15,8 @@ def _get_cache_dir() -> Path:
     return config.get_cache_dir()
 
 
-# In-memory cache
-_memory_cache: dict[str, torch.Tensor] = {}
+# In-memory cache - can store dict (voice prompt) or tensor (legacy)
+_memory_cache: dict[str, Union[torch.Tensor, Dict[str, Any]]] = {}
 
 
 def get_cache_key(audio_path: str, reference_text: str) -> str:
@@ -43,7 +43,7 @@ def get_cache_key(audio_path: str, reference_text: str) -> str:
 
 def get_cached_voice_prompt(
     cache_key: str,
-) -> Optional[torch.Tensor]:
+) -> Optional[Union[torch.Tensor, Dict[str, Any]]]:
     """
     Get cached voice prompt if available.
 
@@ -51,7 +51,7 @@ def get_cached_voice_prompt(
         cache_key: Cache key
 
     Returns:
-        Cached voice prompt tensor or None
+        Cached voice prompt (dict or tensor) or None
     """
     # Check in-memory cache
     if cache_key in _memory_cache:
@@ -73,18 +73,78 @@ def get_cached_voice_prompt(
 
 def cache_voice_prompt(
     cache_key: str,
-    voice_prompt: torch.Tensor,
+    voice_prompt: Union[torch.Tensor, Dict[str, Any]],
 ) -> None:
     """
     Cache voice prompt to memory and disk.
 
     Args:
         cache_key: Cache key
-        voice_prompt: Voice prompt tensor
+        voice_prompt: Voice prompt (dict or tensor)
     """
     # Store in memory
     _memory_cache[cache_key] = voice_prompt
 
-    # Store on disk
+    # Store on disk (torch.save can handle both dicts and tensors)
     cache_file = _get_cache_dir() / f"{cache_key}.prompt"
     torch.save(voice_prompt, cache_file)
+
+
+def clear_voice_prompt_cache() -> int:
+    """
+    Clear all voice prompt caches (memory and disk).
+    
+    Returns:
+        Number of cache files deleted
+    """
+    # Clear memory cache
+    _memory_cache.clear()
+    
+    # Clear disk cache
+    cache_dir = _get_cache_dir()
+    deleted_count = 0
+    
+    if cache_dir.exists():
+        # Delete prompt cache files
+        for cache_file in cache_dir.glob("*.prompt"):
+            try:
+                cache_file.unlink()
+                deleted_count += 1
+            except Exception as e:
+                print(f"Failed to delete cache file {cache_file}: {e}")
+        
+        # Delete combined audio files
+        for audio_file in cache_dir.glob("combined_*.wav"):
+            try:
+                audio_file.unlink()
+                deleted_count += 1
+            except Exception as e:
+                print(f"Failed to delete combined audio file {audio_file}: {e}")
+    
+    return deleted_count
+
+
+def clear_profile_cache(profile_id: str) -> int:
+    """
+    Clear cache files for a specific profile.
+    
+    Args:
+        profile_id: Profile ID
+    
+    Returns:
+        Number of cache files deleted
+    """
+    cache_dir = _get_cache_dir()
+    deleted_count = 0
+    
+    if cache_dir.exists():
+        # Delete combined audio files for this profile
+        pattern = f"combined_{profile_id}_*.wav"
+        for audio_file in cache_dir.glob(pattern):
+            try:
+                audio_file.unlink()
+                deleted_count += 1
+            except Exception as e:
+                print(f"Failed to delete combined audio file {audio_file}: {e}")
+    
+    return deleted_count

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."""
@@ -29,7 +31,7 @@ class HFProgressTracker:
         
         class TrackedTqdm(original_tqdm):
             """A tqdm subclass that reports progress to our tracker."""
-            
+
             def __init__(self, *args, **kwargs):
                 # Extract filename from desc before passing to parent
                 desc = kwargs.get("desc", "")
@@ -80,7 +82,7 @@ class HFProgressTracker:
             
             def update(self, n=1):
                 result = super().update(n)
-                
+
                 # Report progress
                 with tracker._lock:
                     if id(self) in tracker._active_tqdms:
@@ -89,6 +91,16 @@ class HFProgressTracker:
                         total = getattr(self, "total", 0)
                         
                         if total and total > 0:
+                            # Always filter out non-byte progress bars (e.g., "Fetching 12 files")
+                            # These cause crazy percentages because they're counting files, not bytes
+                            if self._is_non_byte_progress(filename):
+                                return result
+                            
+                            # When model is cached, also filter out generation-related progress
+                            if tracker.filter_non_downloads:
+                                if not self._is_download_progress(filename):
+                                    return result
+                            
                             # Update per-file tracking
                             tracker._file_sizes[filename] = total
                             tracker._file_downloaded[filename] = current
@@ -97,6 +109,13 @@ class HFProgressTracker:
                             tracker._total_size = sum(tracker._file_sizes.values())
                             tracker._total_downloaded = sum(tracker._file_downloaded.values())
                             
+                            # Only report progress once we have a meaningful total (at least 1MB)
+                            # This avoids the "100% at 0MB" issue when small config
+                            # files are counted before the real model files
+                            MIN_TOTAL_BYTES = 1_000_000  # 1MB
+                            if tracker._total_size < MIN_TOTAL_BYTES:
+                                return result
+                            
                             # Call progress callback
                             if tracker.progress_callback:
                                 tracker.progress_callback(
@@ -107,6 +126,50 @@ class HFProgressTracker:
                 
                 return result
             
+            def _is_non_byte_progress(self, filename: str) -> bool:
+                """Check if this progress bar should be SKIPPED (returns True to skip).
+                
+                We want to track byte-based progress bars. This method identifies
+                progress bars that count files/items instead of bytes, which would
+                cause crazy percentages if mixed with our byte counting.
+                
+                Returns:
+                    True = SKIP this bar (it's not byte-based)
+                    False = TRACK this bar (it counts bytes)
+                """
+                if not filename:
+                    return False
+                
+                filename_lower = filename.lower()
+                
+                # Skip "Fetching X files" - it counts files (total=12), not bytes
+                # Don't skip "Downloading (incomplete total...)" - that IS byte-based
+                skip_patterns = [
+                    'fetching',  # "Fetching 12 files" has total=12 files, not bytes
+                ]
+                return any(pattern in filename_lower for pattern in skip_patterns)
+            
+            def _is_download_progress(self, filename: str) -> bool:
+                """Check if this is a real file download progress bar vs internal processing."""
+                if not filename or filename == "unknown":
+                    return False
+                
+                # Real downloads have file extensions
+                download_extensions = [
+                    '.safetensors', '.bin', '.pt', '.pth',  # Model weights
+                    '.json', '.txt', '.py',  # Config files
+                    '.msgpack', '.h5',  # Other formats
+                ]
+                
+                filename_lower = filename.lower()
+                has_extension = any(filename_lower.endswith(ext) for ext in download_extensions)
+                
+                # Skip generation-related progress indicators
+                skip_patterns = ['segment', 'processing', 'generating', 'loading']
+                has_skip_pattern = any(pattern in filename_lower for pattern in skip_patterns)
+                
+                return has_extension and not has_skip_pattern
+            
             def close(self):
                 with tracker._lock:
                     if id(self) in tracker._active_tqdms:
@@ -120,7 +183,7 @@ class HFProgressTracker:
         """Context manager to patch tqdm for progress tracking."""
         try:
             import tqdm as tqdm_module
-            
+
             # Store original tqdm class
             self._original_tqdm_class = tqdm_module.tqdm
             
@@ -135,10 +198,10 @@ class HFProgressTracker:
             
             # Create our tracked tqdm class
             tracked_tqdm = self._create_tracked_tqdm_class()
-            
+
             # Patch tqdm.tqdm
             tqdm_module.tqdm = tracked_tqdm
-            
+
             # Also patch tqdm.auto.tqdm if it exists (used by huggingface_hub)
             self._original_tqdm_auto = None
             if hasattr(tqdm_module, "auto") and hasattr(tqdm_module.auto, "tqdm"):
@@ -146,22 +209,79 @@ class HFProgressTracker:
                 tqdm_module.auto.tqdm = tracked_tqdm
             
             # Patch in sys.modules to catch already-imported references
+            # huggingface_hub uses: from tqdm.auto import tqdm as base_tqdm
+            # So we need to patch both 'tqdm' and 'base_tqdm' attributes
             self._patched_modules = {}
+            tqdm_attr_names = ['tqdm', 'base_tqdm', 'old_tqdm']  # Various names used
+            
+            patched_count = 0
             for module_name in list(sys.modules.keys()):
                 if "huggingface" in module_name or module_name.startswith("tqdm"):
                     try:
                         module = sys.modules[module_name]
-                        if hasattr(module, "tqdm"):
-                            attr = getattr(module, "tqdm")
-                            # Only patch if it's the original tqdm class (not already patched)
-                            if attr is self._original_tqdm_class or (
-                                hasattr(attr, "__name__") and attr.__name__ == "tqdm"
-                            ):
-                                self._patched_modules[module_name] = attr
-                                setattr(module, "tqdm", tracked_tqdm)
+                        for attr_name in tqdm_attr_names:
+                            if hasattr(module, attr_name):
+                                attr = getattr(module, attr_name)
+                                # Only patch if it's a tqdm class (not already patched)
+                                is_tqdm_class = (
+                                    attr is self._original_tqdm_class or 
+                                    (self._original_tqdm_auto and attr is self._original_tqdm_auto) or
+                                    (hasattr(attr, "__name__") and attr.__name__ == "tqdm" and 
+                                     hasattr(attr, "update"))  # tqdm classes have update method
+                                )
+                                if is_tqdm_class:
+                                    key = f"{module_name}.{attr_name}"
+                                    self._patched_modules[key] = (module, attr_name, attr)
+                                    setattr(module, attr_name, tracked_tqdm)
+                                    patched_count += 1
                     except (AttributeError, TypeError):
                         pass
             
+            # ALSO monkey-patch the update method on huggingface_hub's tqdm class
+            # This is needed because the class was already defined at import time
+            self._hf_tqdm_original_update = None
+            try:
+                from huggingface_hub.utils import tqdm as hf_tqdm_module
+                if hasattr(hf_tqdm_module, 'tqdm'):
+                    hf_tqdm_class = hf_tqdm_module.tqdm
+                    self._hf_tqdm_original_update = hf_tqdm_class.update
+                    
+                    # Create a wrapper that calls our tracking
+                    tracker = self  # Reference to HFProgressTracker instance
+                    def patched_update(tqdm_self, n=1):
+                        result = tracker._hf_tqdm_original_update(tqdm_self, n)
+                        
+                        # Track this progress
+                        with tracker._lock:
+                            desc = getattr(tqdm_self, 'desc', '') or ''
+                            current = getattr(tqdm_self, 'n', 0)
+                            total = getattr(tqdm_self, 'total', 0) or 0
+                            
+                            # Skip non-byte progress bars
+                            if 'fetching' in desc.lower():
+                                return result
+                            
+                            # Skip until we have a meaningful total (at least 1MB)
+                            # This avoids the "100% at 0MB" issue when small config
+                            # files are counted before the real model files
+                            MIN_TOTAL_BYTES = 1_000_000  # 1MB
+                            if total >= MIN_TOTAL_BYTES:
+                                tracker._total_downloaded = current
+                                tracker._total_size = total
+                                
+                                if tracker.progress_callback:
+                                    tracker.progress_callback(current, total, desc)
+                        
+                        return result
+                    
+                    hf_tqdm_class.update = patched_update
+                    patched_count += 1
+                    print(f"[HFProgressTracker] Monkey-patched huggingface_hub.utils.tqdm.tqdm.update")
+            except (ImportError, AttributeError) as e:
+                print(f"[HFProgressTracker] Could not monkey-patch hf_tqdm: {e}")
+            
+            print(f"[HFProgressTracker] Patched {patched_count} tqdm references")
+            
             yield
             
         except ImportError:
@@ -178,15 +298,24 @@ class HFProgressTracker:
                         tqdm_module.auto.tqdm = self._original_tqdm_auto
                     
                     # Restore patched modules
-                    for module_name, original in self._patched_modules.items():
+                    for key, (module, attr_name, original) in self._patched_modules.items():
                         try:
-                            module = sys.modules.get(module_name)
                             if module and original:
-                                setattr(module, "tqdm", original)
+                                setattr(module, attr_name, original)
                         except (AttributeError, TypeError):
                             pass
                     self._patched_modules = {}
                     
+                    # Restore hf_tqdm's original update method
+                    if self._hf_tqdm_original_update:
+                        try:
+                            from huggingface_hub.utils import tqdm as hf_tqdm_module
+                            if hasattr(hf_tqdm_module, 'tqdm'):
+                                hf_tqdm_module.tqdm.update = self._hf_tqdm_original_update
+                        except (ImportError, AttributeError):
+                            pass
+                        self._hf_tqdm_original_update = None
+                    
                 except (ImportError, AttributeError):
                     pass
 
@@ -194,13 +323,17 @@ class HFProgressTracker:
 def create_hf_progress_callback(model_name: str, progress_manager):
     """Create a progress callback for HuggingFace downloads."""
     def callback(downloaded: int, total: int, filename: str = ""):
-        """Progress callback."""
-        if total > 0:
-            progress_manager.update_progress(
-                model_name=model_name,
-                current=downloaded,
-                total=total,
-                filename=filename or "",
-                status="downloading",
-            )
+        """Progress callback.
+        
+        Note: We send updates even when total=0 (unknown) to provide feedback
+        during the "incomplete total" phase of huggingface_hub downloads.
+        The frontend handles total=0 gracefully.
+        """
+        progress_manager.update_progress(
+            model_name=model_name,
+            current=downloaded,
+            total=total,
+            filename=filename or "",
+            status="downloading",
+        )
     return callback

backend/utils/images.py

@@ -0,0 +1,114 @@
+"""Image processing utilities for avatar uploads."""
+
+from pathlib import Path
+from typing import Optional, Tuple
+from PIL import Image
+
+# JPEG can be reported as 'JPEG' or 'MPO' (for multi-picture format from some cameras)
+ALLOWED_FORMATS = {'PNG', 'JPEG', 'WEBP', 'MPO', 'JPG'}
+MAX_SIZE = 512
+MAX_FILE_SIZE = 5 * 1024 * 1024  # 5MB
+
+
+def validate_image(file_path: str) -> Tuple[bool, Optional[str]]:
+    """
+    Validate image format and file size.
+    
+    Args:
+        file_path: Path to image file
+        
+    Returns:
+        Tuple of (is_valid, error_message)
+    """
+    path = Path(file_path)
+    
+    # Check file size
+    if path.stat().st_size > MAX_FILE_SIZE:
+        return False, f"File size exceeds maximum of {MAX_FILE_SIZE // (1024 * 1024)}MB"
+    
+    try:
+        with Image.open(file_path) as img:
+            # Verify the image can be loaded
+            img.load()
+            
+            # Check format (normalize JPEG variants)
+            img_format = img.format
+            if img_format in ('MPO', 'JPG'):
+                img_format = 'JPEG'
+            
+            if img_format not in {'PNG', 'JPEG', 'WEBP'}:
+                return False, f"Invalid format '{img_format}'. Allowed formats: PNG, JPEG, WEBP"
+            
+            return True, None
+    except Exception as e:
+        return False, f"Invalid image file: {str(e)}"
+
+
+def process_avatar(input_path: str, output_path: str, max_size: int = MAX_SIZE) -> None:
+    """
+    Process avatar image: resize and optimize.
+    
+    Resizes image to fit within max_size x max_size while maintaining aspect ratio.
+    
+    Args:
+        input_path: Path to input image
+        output_path: Path to save processed image
+        max_size: Maximum width or height in pixels
+    """
+    with Image.open(input_path) as img:
+        # Handle EXIF orientation for JPEG images
+        try:
+            from PIL import ExifTags
+            for orientation in ExifTags.TAGS.keys():
+                if ExifTags.TAGS[orientation] == 'Orientation':
+                    break
+            exif = img._getexif()
+            if exif is not None:
+                orientation_value = exif.get(orientation)
+                if orientation_value == 3:
+                    img = img.rotate(180, expand=True)
+                elif orientation_value == 6:
+                    img = img.rotate(270, expand=True)
+                elif orientation_value == 8:
+                    img = img.rotate(90, expand=True)
+        except (AttributeError, KeyError, IndexError, TypeError):
+            # No EXIF data or orientation tag
+            pass
+        
+        # Convert to RGB if necessary (handles RGBA, P, CMYK, etc.)
+        if img.mode not in ('RGB', 'L'):
+            if img.mode == 'RGBA':
+                # Create white background for RGBA images
+                background = Image.new('RGB', img.size, (255, 255, 255))
+                background.paste(img, mask=img.split()[3])  # Use alpha channel as mask
+                img = background
+            elif img.mode == 'CMYK':
+                # Convert CMYK to RGB
+                img = img.convert('RGB')
+            elif img.mode == 'P':
+                # Convert palette mode to RGB
+                img = img.convert('RGB')
+            else:
+                img = img.convert('RGB')
+        
+        # Calculate new size maintaining aspect ratio
+        img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
+        
+        # Determine output format from extension
+        output_ext = Path(output_path).suffix.lower()
+        
+        format_map = {
+            '.png': 'PNG',
+            '.jpeg': 'JPEG',
+            '.jpg': 'JPEG',
+            '.webp': 'WEBP'
+        }
+        
+        output_format = format_map.get(output_ext, 'PNG')
+        
+        # Save with optimization
+        save_kwargs = {'optimize': True}
+        if output_format == 'JPEG':
+            save_kwargs['quality'] = 90
+        
+        img.save(output_path, format=output_format, **save_kwargs)

backend/utils/progress.py

@@ -6,16 +6,61 @@ from typing import Optional, Callable, Dict, List
 from fastapi.responses import StreamingResponse
 import asyncio
 import json
+import threading
 from datetime import datetime
 
 
 class ProgressManager:
-    """Manages download progress for multiple models."""
+    """Manages download progress for multiple models.
+    
+    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."""
+        self._main_loop = loop
+    
+    def _notify_listeners_threadsafe(self, model_name: str, progress_data: Dict):
+        """Notify listeners in a thread-safe manner."""
+        import logging
+        logger = logging.getLogger(__name__)
+        
+        if model_name not in self._listeners:
+            return
+            
+        for queue in self._listeners[model_name]:
+            try:
+                # Check if we're in the main event loop thread
+                try:
+                    running_loop = asyncio.get_running_loop()
+                    # We're in an async context, can use put_nowait directly
+                    queue.put_nowait(progress_data.copy())
+                except RuntimeError:
+                    # Not in async context (running in background thread)
+                    # Use call_soon_threadsafe to safely put on queue
+                    if self._main_loop and self._main_loop.is_running():
+                        self._main_loop.call_soon_threadsafe(
+                            lambda q=queue, d=progress_data.copy(): q.put_nowait(d) if not q.full() else None
+                        )
+                    else:
+                        logger.debug(f"No main loop available for {model_name}, skipping notification")
+            except asyncio.QueueFull:
+                logger.warning(f"Queue full for {model_name}, dropping update")
+            except Exception as e:
+                logger.warning(f"Error notifying listener for {model_name}: {e}")
+
     def update_progress(
         self,
         model_name: str,
@@ -26,7 +71,13 @@ 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")
             current: Current bytes downloaded
@@ -34,9 +85,20 @@ class ProgressManager:
             filename: Current file being downloaded
             status: Status string (downloading, extracting, complete, error)
         """
-        progress_pct = (current / total * 100) if total > 0 else 0
-        
-        self._progress[model_name] = {
+        import logging
+        import time
+        logger = logging.getLogger(__name__)
+
+        # 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,
             "current": current,
             "total": total,
@@ -45,26 +107,56 @@ class ProgressManager:
             "status": status,
             "timestamp": datetime.now().isoformat(),
         }
+
+        # Thread-safe update of progress dict (always update internal state)
+        with self._lock:
+            self._progress[model_name] = progress_data
+
+        # Check if we should notify listeners (throttling)
+        current_time = time.time()
+        last_time = self._last_notify_time.get(model_name, 0)
+        last_progress = self._last_notify_progress.get(model_name, -100)
         
-        # Notify all listeners
-        if model_name in self._listeners:
-            for queue in self._listeners[model_name]:
-                try:
-                    queue.put_nowait(self._progress[model_name].copy())
-                except asyncio.QueueFull:
-                    pass
+        time_delta = current_time - last_time
+        progress_delta = abs(progress_pct - last_progress)
+        
+        # Always notify for complete/error status, or if throttle conditions are met
+        should_notify = (
+            status in ("complete", "error") or
+            time_delta >= self.THROTTLE_INTERVAL_SECONDS or
+            progress_delta >= self.THROTTLE_PROGRESS_DELTA
+        )
+        
+        if not should_notify:
+            return  # Skip this update (throttled)
+        
+        # Update throttle tracking
+        self._last_notify_time[model_name] = current_time
+        self._last_notify_progress[model_name] = progress_pct
+
+        # Notify all listeners (thread-safe)
+        listener_count = len(self._listeners.get(model_name, []))
+
+        if listener_count > 0:
+            logger.debug(f"Notifying {listener_count} listeners for {model_name}: {progress_pct:.1f}% ({filename})")
+            self._notify_listeners_threadsafe(model_name, progress_data)
+        else:
+            logger.debug(f"No listeners for {model_name}, progress update stored: {progress_pct:.1f}%")
     
     def get_progress(self, model_name: str) -> Optional[Dict]:
-        """Get current progress for a model."""
-        return self._progress.get(model_name)
+        """Get current progress for a model. Thread-safe."""
+        with self._lock:
+            progress = self._progress.get(model_name)
+            return progress.copy() if progress else None
     
     def get_all_active(self) -> List[Dict]:
-        """Get all active downloads (status is 'downloading' or 'extracting')."""
+        """Get all active downloads (status is 'downloading' or 'extracting'). Thread-safe."""
         active = []
-        for model_name, progress in self._progress.items():
-            status = progress.get("status", "")
-            if status in ("downloading", "extracting"):
-                active.append(progress.copy())
+        with self._lock:
+            for model_name, progress in self._progress.items():
+                status = progress.get("status", "")
+                if status in ("downloading", "extracting"):
+                    active.append(progress.copy())
         return active
     
     def create_progress_callback(self, model_name: str, filename: Optional[str] = None):
@@ -98,30 +190,57 @@ class ProgressManager:
     async def subscribe(self, model_name: str):
         """
         Subscribe to progress updates for a model.
-        
+
         Yields progress updates as Server-Sent Events.
         """
-        queue = asyncio.Queue(maxsize=10)
+        import logging
+        logger = logging.getLogger(__name__)
         
+        # Store the main event loop for thread-safe operations
+        try:
+            self._main_loop = asyncio.get_running_loop()
+        except RuntimeError:
+            pass
+
+        queue = asyncio.Queue(maxsize=10)
+
         # Add to listeners
         if model_name not in self._listeners:
             self._listeners[model_name] = []
         self._listeners[model_name].append(queue)
-        
+
+        logger.info(f"SSE client subscribed to {model_name}, total listeners: {len(self._listeners[model_name])}")
+
         try:
-            # Send initial progress if available
-            if model_name in self._progress:
-                yield f"data: {json.dumps(self._progress[model_name])}\n\n"
+            # Send initial progress if available and still in progress (thread-safe read)
+            with self._lock:
+                initial_progress = self._progress.get(model_name)
+                if initial_progress:
+                    initial_progress = initial_progress.copy()
             
+            if initial_progress:
+                status = initial_progress.get('status')
+                # Only send initial progress if download is actually in progress
+                # Don't send old 'complete' or 'error' status from previous downloads
+                if status in ('downloading', 'extracting'):
+                    logger.info(f"Sending initial progress for {model_name}: {status}")
+                    yield f"data: {json.dumps(initial_progress)}\n\n"
+                else:
+                    logger.info(f"Skipping initial progress for {model_name} (status: {status})")
+            else:
+                logger.info(f"No initial progress available for {model_name}")
+
             # Stream updates
             while True:
                 try:
                     # Wait for update with timeout
                     progress = await asyncio.wait_for(queue.get(), timeout=1.0)
+                    logger.debug(f"Sending progress update for {model_name}: {progress.get('status')} - {progress.get('progress', 0):.1f}%")
                     yield f"data: {json.dumps(progress)}\n\n"
-                    
+
                     # Stop if complete or error
                     if progress.get("status") in ("complete", "error"):
+                        logger.info(f"Download {progress.get('status')} for {model_name}, closing SSE connection")
                         break
                 except asyncio.TimeoutError:
                     # Send heartbeat
@@ -133,32 +252,53 @@ class ProgressManager:
                 self._listeners[model_name].remove(queue)
                 if not self._listeners[model_name]:
                     del self._listeners[model_name]
+                logger.info(f"SSE client unsubscribed from {model_name}, remaining listeners: {len(self._listeners.get(model_name, []))}")
     
     def mark_complete(self, model_name: str):
-        """Mark a model download as complete."""
-        if model_name in self._progress:
-            self._progress[model_name]["status"] = "complete"
-            self._progress[model_name]["progress"] = 100.0
-            # Notify listeners
-            if model_name in self._listeners:
-                for queue in self._listeners[model_name]:
-                    try:
-                        queue.put_nowait(self._progress[model_name].copy())
-                    except asyncio.QueueFull:
-                        pass
+        """Mark a model download as complete. Thread-safe."""
+        import logging
+        logger = logging.getLogger(__name__)
+
+        with self._lock:
+            if model_name in self._progress:
+                self._progress[model_name]["status"] = "complete"
+                self._progress[model_name]["progress"] = 100.0
+                progress_data = self._progress[model_name].copy()
+            else:
+                logger.warning(f"Cannot mark {model_name} as complete: not found in progress")
+                return
+        
+        logger.info(f"Marked {model_name} as complete")
+        # Notify listeners (thread-safe)
+        self._notify_listeners_threadsafe(model_name, progress_data)
     
     def mark_error(self, model_name: str, error: str):
-        """Mark a model download as failed."""
-        if model_name in self._progress:
-            self._progress[model_name]["status"] = "error"
-            self._progress[model_name]["error"] = error
-            # Notify listeners
-            if model_name in self._listeners:
-                for queue in self._listeners[model_name]:
-                    try:
-                        queue.put_nowait(self._progress[model_name].copy())
-                    except asyncio.QueueFull:
-                        pass
+        """Mark a model download as failed. Thread-safe."""
+        import logging
+        logger = logging.getLogger(__name__)
+
+        with self._lock:
+            if model_name in self._progress:
+                self._progress[model_name]["status"] = "error"
+                self._progress[model_name]["error"] = error
+                progress_data = self._progress[model_name].copy()
+            else:
+                # Create new progress entry for error
+                progress_data = {
+                    "model_name": model_name,
+                    "current": 0,
+                    "total": 0,
+                    "progress": 0,
+                    "filename": None,
+                    "status": "error",
+                    "error": error,
+                    "timestamp": datetime.now().isoformat(),
+                }
+                self._progress[model_name] = progress_data
+        
+        logger.error(f"Marked {model_name} as error: {error}")
+        # Notify listeners (thread-safe)
+        self._notify_listeners_threadsafe(model_name, progress_data)
 
 
 # Global progress manager instance

backend/voicebox-server.spec

@@ -4,16 +4,20 @@ from PyInstaller.utils.hooks import collect_submodules
 from PyInstaller.utils.hooks import copy_metadata
 
 datas = []
-hiddenimports = ['backend', 'backend.main', 'backend.config', 'backend.database', 'backend.models', 'backend.profiles', 'backend.history', 'backend.tts', 'backend.transcribe', 'backend.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']
+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')
+datas += collect_data_files('mlx_audio')
 datas += copy_metadata('qwen-tts')
 hiddenimports += collect_submodules('qwen_tts')
 hiddenimports += collect_submodules('jaraco')
+hiddenimports += collect_submodules('mlx')
+hiddenimports += collect_submodules('mlx_audio')
 
 
 a = Analysis(
     ['server.py'],
-    pathex=['C:\\Users\\ijame\\Projects\\voice\\Qwen3-TTS'],
+    pathex=[],
     binaries=[],
     datas=datas,
     hiddenimports=hiddenimports,

bun.lock

@@ -13,8 +13,11 @@
     },
     "app": {
       "name": "@voicebox/app",
-      "version": "0.1.0",
+      "version": "0.1.11",
       "dependencies": {
+        "@dnd-kit/core": "^6.3.1",
+        "@dnd-kit/sortable": "^10.0.0",
+        "@dnd-kit/utilities": "^3.2.2",
         "@hookform/resolvers": "^3.9.0",
         "@radix-ui/react-alert-dialog": "^1.1.1",
         "@radix-ui/react-avatar": "^1.1.0",
@@ -32,6 +35,7 @@
         "@radix-ui/react-toast": "^1.2.1",
         "@tanstack/react-query": "^5.0.0",
         "@tanstack/react-query-devtools": "^5.0.0",
+        "@tanstack/react-router": "^1.157.16",
         "@tauri-apps/api": "^2.0.0",
         "@tauri-apps/plugin-dialog": "^2.0.0",
         "@tauri-apps/plugin-fs": "^2.0.0",
@@ -46,6 +50,7 @@
         "react": "^18.3.0",
         "react-dom": "^18.3.0",
         "react-hook-form": "^7.53.0",
+        "react-sound-visualizer": "^1.4.0",
         "tailwind-merge": "^2.5.4",
         "wavesurfer.js": "^7.0.0",
         "zod": "^3.23.8",
@@ -63,7 +68,7 @@
     },
     "landing": {
       "name": "@voicebox/landing",
-      "version": "0.1.0",
+      "version": "0.1.11",
       "dependencies": {
         "@radix-ui/react-separator": "^1.1.8",
         "@radix-ui/react-slot": "^1.2.4",
@@ -88,10 +93,14 @@
     },
     "tauri": {
       "name": "@voicebox/tauri",
-      "version": "0.1.0",
+      "version": "0.1.11",
       "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",
@@ -107,7 +116,7 @@
     },
     "web": {
       "name": "@voicebox/web",
-      "version": "0.1.0",
+      "version": "0.1.11",
       "dependencies": {
         "@tanstack/react-query": "^5.0.0",
         "react": "^18.3.0",
@@ -188,6 +197,14 @@
 
     "@biomejs/cli-win32-x64": ["@biomejs/[email protected]", "", { "os": "win32", "cpu": "x64" }, "sha512-qqGVWqNNek0KikwPZlOIoxtXgsNGsX+rgdEzgw82Re8nF02W+E2WokaQhpF5TdBh/D/RQ3TLppH+otp6ztN0lw=="],
 
+    "@dnd-kit/accessibility": ["@dnd-kit/[email protected]", "", { "dependencies": { "tslib": "^2.0.0" }, "peerDependencies": { "react": ">=16.8.0" } }, "sha512-2P+YgaXF+gRsIihwwY1gCsQSYnu9Zyj2py8kY5fFvUM1qm2WA2u639R6YNVfU4GWr+ZM5mqEsfHZZLoRONbemw=="],
+
+    "@dnd-kit/core": ["@dnd-kit/[email protected]", "", { "dependencies": { "@dnd-kit/accessibility": "^3.1.1", "@dnd-kit/utilities": "^3.2.2", "tslib": "^2.0.0" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-xkGBRQQab4RLwgXxoqETICr6S5JlogafbhNsidmrkVv2YRs5MLwpjoF2qpiGjQt8S9AoxtIV603s0GIUpY5eYQ=="],
+
+    "@dnd-kit/sortable": ["@dnd-kit/[email protected]", "", { "dependencies": { "@dnd-kit/utilities": "^3.2.2", "tslib": "^2.0.0" }, "peerDependencies": { "@dnd-kit/core": "^6.3.0", "react": ">=16.8.0" } }, "sha512-+xqhmIIzvAYMGfBYYnbKuNicfSsk4RksY2XdmJhT+HAC01nix6fHCztU68jooFiMUB01Ky3F0FyOvhG/BZrWkg=="],
+
+    "@dnd-kit/utilities": ["@dnd-kit/[email protected]", "", { "dependencies": { "tslib": "^2.0.0" }, "peerDependencies": { "react": ">=16.8.0" } }, "sha512-+MKAJEOfaBe5SmV6t34p80MMKhjvUz0vRrvVJbPT0WElzaOJ/1xs+D+KDv+tD/NE5ujfrChEcshd4fLn0wpiqg=="],
+
     "@emnapi/runtime": ["@emnapi/[email protected]", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-mehfKSMWjjNol8659Z8KxEMrdSJDDot5SXMq00dM8BN4o+CLNXQ0xH2V7EchNHV4RmbZLmmPdEaXZc5H2FXmDg=="],
 
     "@esbuild/aix-ppc64": ["@esbuild/[email protected]", "", { "os": "aix", "cpu": "ppc64" }, "sha512-1SDgH6ZSPTlggy1yI6+Dbkiz8xzpHJEVAlF/AM1tHPLsf5STom9rwtjE4hKAF20FfXXNTFqEYXyJNWh1GiZedQ=="],
@@ -512,6 +529,8 @@
 
     "@tailwindcss/vite": ["@tailwindcss/[email protected]", "", { "dependencies": { "@tailwindcss/node": "4.1.18", "@tailwindcss/oxide": "4.1.18", "tailwindcss": "4.1.18" }, "peerDependencies": { "vite": "^5.2.0 || ^6 || ^7" } }, "sha512-jVA+/UpKL1vRLg6Hkao5jldawNmRo7mQYrZtNHMIVpLfLhDml5nMRUo/8MwoX2vNXvnaXNNMedrMfMugAVX1nA=="],
 
+    "@tanstack/history": ["@tanstack/[email protected]", "", {}, "sha512-xyIfof8eHBuub1CkBnbKNKQXeRZC4dClhmzePHVOEel4G7lk/dW+TQ16da7CFdeNLv6u6Owf5VoBQxoo6DFTSA=="],
+
     "@tanstack/query-core": ["@tanstack/[email protected]", "", {}, "sha512-OMD2HLpNouXEfZJWcKeVKUgQ5n+n3A2JFmBaScpNDUqSrQSjiveC7dKMe53uJUg1nDG16ttFPz2xfilz6i2uVg=="],
 
     "@tanstack/query-devtools": ["@tanstack/[email protected]", "", {}, "sha512-N8D27KH1vEpVacvZgJL27xC6yPFUy0Zkezn5gnB3L3gRCxlDeSuiya7fKge8Y91uMTnC8aSxBQhcK6ocY7alpQ=="],
@@ -520,6 +539,14 @@
 
     "@tanstack/react-query-devtools": ["@tanstack/[email protected]", "", { "dependencies": { "@tanstack/query-devtools": "5.92.0" }, "peerDependencies": { "@tanstack/react-query": "^5.90.14", "react": "^18 || ^19" } }, "sha512-ZJ1503ay5fFeEYFUdo7LMNFzZryi6B0Cacrgr2h1JRkvikK1khgIq6Nq2EcblqEdIlgB/r7XDW8f8DQ89RuUgg=="],
 
+    "@tanstack/react-router": ["@tanstack/[email protected]", "", { "dependencies": { "@tanstack/history": "1.154.14", "@tanstack/react-store": "^0.8.0", "@tanstack/router-core": "1.157.16", "isbot": "^5.1.22", "tiny-invariant": "^1.3.3", "tiny-warning": "^1.0.3" }, "peerDependencies": { "react": ">=18.0.0 || >=19.0.0", "react-dom": ">=18.0.0 || >=19.0.0" } }, "sha512-xwFQa7S7dhBhm3aJYwU79cITEYgAKSrcL6wokaROIvl2JyIeazn8jueWqUPJzFjv+QF6Q8euKRlKUEyb5q2ymg=="],
+
+    "@tanstack/react-store": ["@tanstack/[email protected]", "", { "dependencies": { "@tanstack/store": "0.8.0", "use-sync-external-store": "^1.6.0" }, "peerDependencies": { "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0", "react-dom": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" } }, "sha512-1vG9beLIuB7q69skxK9r5xiLN3ztzIPfSQSs0GfeqWGO2tGIyInZx0x1COhpx97RKaONSoAb8C3dxacWksm1ow=="],
+
+    "@tanstack/router-core": ["@tanstack/[email protected]", "", { "dependencies": { "@tanstack/history": "1.154.14", "@tanstack/store": "^0.8.0", "cookie-es": "^2.0.0", "seroval": "^1.4.2", "seroval-plugins": "^1.4.2", "tiny-invariant": "^1.3.3", "tiny-warning": "^1.0.3" } }, "sha512-eJuVgM7KZYTTr4uPorbUzUflmljMVcaX2g6VvhITLnHmg9SBx9RAgtQ1HmT+72mzyIbRSlQ1q0fY/m+of/fosA=="],
+
+    "@tanstack/store": ["@tanstack/[email protected]", "", {}, "sha512-Om+BO0YfMZe//X2z0uLF2j+75nQga6TpTJgLJQBiq85aOyZNIhkCgleNcud2KQg4k4v9Y9l+Uhru3qWMPGTOzQ=="],
+
     "@tauri-apps/api": ["@tauri-apps/[email protected]", "", {}, "sha512-IGlhP6EivjXHepbBic618GOmiWe4URJiIeZFlB7x3czM0yDHHYviH1Xvoiv4FefdkQtn6v7TuwWCRfOGdnVUGw=="],
 
     "@tauri-apps/cli": ["@tauri-apps/[email protected]", "", { "optionalDependencies": { "@tauri-apps/cli-darwin-arm64": "2.9.6", "@tauri-apps/cli-darwin-x64": "2.9.6", "@tauri-apps/cli-linux-arm-gnueabihf": "2.9.6", "@tauri-apps/cli-linux-arm64-gnu": "2.9.6", "@tauri-apps/cli-linux-arm64-musl": "2.9.6", "@tauri-apps/cli-linux-riscv64-gnu": "2.9.6", "@tauri-apps/cli-linux-x64-gnu": "2.9.6", "@tauri-apps/cli-linux-x64-musl": "2.9.6", "@tauri-apps/cli-win32-arm64-msvc": "2.9.6", "@tauri-apps/cli-win32-ia32-msvc": "2.9.6", "@tauri-apps/cli-win32-x64-msvc": "2.9.6" }, "bin": { "tauri": "tauri.js" } }, "sha512-3xDdXL5omQ3sPfBfdC8fCtDKcnyV7OqyzQgfyT5P3+zY6lcPqIYKQBvUasNvppi21RSdfhy44ttvJmftb0PCDw=="],
@@ -664,6 +691,8 @@
 
     "convert-source-map": ["[email protected]", "", {}, "sha512-Kvp459HrV2FEJ1CAsi1Ku+MY3kasH19TFykTz2xWmMeq6bk2NU3XXvfJ+Q61m0xktWwt+1HSYf3JZsTms3aRJg=="],
 
+    "cookie-es": ["[email protected]", "", {}, "sha512-RAj4E421UYRgqokKUmotqAwuplYw15qtdXfY+hGzgCJ/MBjCVZcSoHK/kH9kocfjRjcDME7IiDWR/1WX1TM2Pg=="],
+
     "cross-spawn": ["[email protected]", "", { "dependencies": { "path-key": "^3.1.0", "shebang-command": "^2.0.0", "which": "^2.0.1" } }, "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA=="],
 
     "cssesc": ["[email protected]", "", { "bin": { "cssesc": "bin/cssesc" } }, "sha512-/Tb/JcjK111nNScGob5MNtsntNM1aCNUDipB/TkwZFhyDrrE47SOx/18wF2bbjgc3ZzCSKW1T5nt5EbFoAz/Vg=="],
@@ -792,6 +821,8 @@
 
     "is-path-inside": ["[email protected]", "", {}, "sha512-Fd4gABb+ycGAmKou8eMftCupSir5lRxqf4aD/vd0cD2qc4HL07OjCeuHMr8Ro4CoMaeCKDB0/ECBOVWjTwUvPQ=="],
 
+    "isbot": ["[email protected]", "", {}, "sha512-aCMIBSKd/XPRYdiCQTLC8QHH4YT8B3JUADu+7COgYIZPvkeoMcUHMRjZLM9/7V8fCj+l7FSREc1lOPNjzogo/A=="],
+
     "isexe": ["[email protected]", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
 
     "jiti": ["[email protected]", "", { "bin": { "jiti": "bin/jiti.js" } }, "sha512-/imKNG4EbWNrVjoNC/1H5/9GFy+tqjGBHCaSsN+P2RnPqjsLmv6UD3Ej+Kj8nBWaRAwyk7kK5ZUc+OEatnTR3A=="],
@@ -944,6 +975,8 @@
 
     "react-remove-scroll-bar": ["[email protected]", "", { "dependencies": { "react-style-singleton": "^2.2.2", "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" }, "optionalPeers": ["@types/react"] }, "sha512-9r+yi9+mgU33AKcj6IbT9oRCO78WriSj6t/cF8DWBZJ9aOGPOTEDvdUDz1FwKim7QXWwmHqtdHnRJfhAxEG46Q=="],
 
+    "react-sound-visualizer": ["[email protected]", "", { "dependencies": { "sound-visualizer": "^1.2.0" }, "peerDependencies": { "react": ">= 16" } }, "sha512-Qe7tFTd1owtQ8nYrUYXg7QLt8mw7iUy86mqj/+IwmXzSw+NlhnMnAGPuisb1Lk3ncliFnM+AQbZb3C4RQN9uMQ=="],
+
     "react-style-singleton": ["[email protected]", "", { "dependencies": { "get-nonce": "^1.0.0", "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-b6jSvxvVnyptAiLjbkWLE/lOnR4lfTtDAl+eUC7RZy+QQWc6wRzIV2CE6xBuMmDxc2qIihtDCZD5NPOFl7fRBQ=="],
 
     "read-cache": ["[email protected]", "", { "dependencies": { "pify": "^2.3.0" } }, "sha512-Owdv/Ft7IjOgm/i0xvNDZ1LrRANRfew4b2prF3OWMQLxLfu3bS8FVhCsrSCMK4lR56Y9ya+AThoTpDCTxCmpRA=="],
@@ -966,6 +999,10 @@
 
     "semver": ["[email protected]", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA=="],
 
+    "seroval": ["[email protected]", "", {}, "sha512-OE4cvmJ1uSPrKorFIH9/w/Qwuvi/IMcGbv5RKgcJ/zjA/IohDLU6SVaxFN9FwajbP7nsX0dQqMDes1whk3y+yw=="],
+
+    "seroval-plugins": ["[email protected]", "", { "peerDependencies": { "seroval": "^1.0" } }, "sha512-EAHqADIQondwRZIdeW2I636zgsODzoBDwb3PT/+7TLDWyw1Dy/Xv7iGUIEXXav7usHDE9HVhOU61irI3EnyyHA=="],
+
     "sharp": ["[email protected]", "", { "dependencies": { "@img/colour": "^1.0.0", "detect-libc": "^2.1.2", "semver": "^7.7.3" }, "optionalDependencies": { "@img/sharp-darwin-arm64": "0.34.5", "@img/sharp-darwin-x64": "0.34.5", "@img/sharp-libvips-darwin-arm64": "1.2.4", "@img/sharp-libvips-darwin-x64": "1.2.4", "@img/sharp-libvips-linux-arm": "1.2.4", "@img/sharp-libvips-linux-arm64": "1.2.4", "@img/sharp-libvips-linux-ppc64": "1.2.4", "@img/sharp-libvips-linux-riscv64": "1.2.4", "@img/sharp-libvips-linux-s390x": "1.2.4", "@img/sharp-libvips-linux-x64": "1.2.4", "@img/sharp-libvips-linuxmusl-arm64": "1.2.4", "@img/sharp-libvips-linuxmusl-x64": "1.2.4", "@img/sharp-linux-arm": "0.34.5", "@img/sharp-linux-arm64": "0.34.5", "@img/sharp-linux-ppc64": "0.34.5", "@img/sharp-linux-riscv64": "0.34.5", "@img/sharp-linux-s390x": "0.34.5", "@img/sharp-linux-x64": "0.34.5", "@img/sharp-linuxmusl-arm64": "0.34.5", "@img/sharp-linuxmusl-x64": "0.34.5", "@img/sharp-wasm32": "0.34.5", "@img/sharp-win32-arm64": "0.34.5", "@img/sharp-win32-ia32": "0.34.5", "@img/sharp-win32-x64": "0.34.5" } }, "sha512-Ou9I5Ft9WNcCbXrU9cMgPBcCK8LiwLqcbywW3t4oDV37n1pzpuNLsYiAV8eODnjbtQlSDwZ2cUEeQz4E54Hltg=="],
 
     "shebang-command": ["[email protected]", "", { "dependencies": { "shebang-regex": "^3.0.0" } }, "sha512-kHxr2zZpYtdmrN1qDjrrX/Z1rR1kG8Dx+gkpK1G4eXmvXswmcE1hTWBWYUzlraYw1/yZp6YuDY77YtvbN0dmDA=="],
@@ -974,6 +1011,8 @@
 
     "slash": ["[email protected]", "", {}, "sha512-g9Q1haeby36OSStwb4ntCGGGaKsaVSjQ68fBxoQcutl5fS1vuY18H3wSt3jFyFtrkx+Kz0V1G85A4MyAdDMi2Q=="],
 
+    "sound-visualizer": ["[email protected]", "", {}, "sha512-2+Un0PrrBgXylnCjrVYUoRW7KEDH29h7O8/MGzeDOgFGBPb9oX/2n/RGBxJXvVv2U3KFwX5olUWeJKf0Rr5TLQ=="],
+
     "source-map-js": ["[email protected]", "", {}, "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA=="],
 
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@@ -1002,6 +1041,10 @@
 
     "thenify-all": ["[email protected]", "", { "dependencies": { "thenify": ">= 3.1.0 < 4" } }, "sha512-RNxQH/qI8/t3thXJDwcstUO4zeqo64+Uy/+sNVRBx4Xn2OX+OZ9oP+iJnNFqplFra2ZUVeKCSa2oVWi3T4uVmA=="],
 
+    "tiny-invariant": ["[email protected]", "", {}, "sha512-+FbBPE1o9QAYvviau/qC5SE3caw21q3xkvWKBtja5vgqOWIHHJ3ioaq1VPfn/Szqctz2bU/oYeKd9/z5BL+PVg=="],
+
+    "tiny-warning": ["[email protected]", "", {}, "sha512-lBN9zLN/oAf68o3zNXYrdCt1kP8WsiGW8Oo2ka41b2IM5JL/S1CTyX1rW0mb/zSuJun0ZUrDxx4sqvYS2FWzPA=="],
+
     "tinyglobby": ["[email protected]", "", { "dependencies": { "fdir": "^6.5.0", "picomatch": "^4.0.3" } }, "sha512-j2Zq4NyQYG5XMST4cbs02Ak8iJUdxRM0XI5QyxXuZOzKOINmWurp3smXu3y5wDcJrptwpSjgXHzIQxR0omXljQ=="],
 
     "to-regex-range": ["[email protected]", "", { "dependencies": { "is-number": "^7.0.0" } }, "sha512-65P7iz6X5yEr1cwcgvQxbbIw7Uk3gOy5dIdtZ4rDveLqhrdJP+Li/Hx6tyK0NEb+2GCyneCMJiGqrADCSNk8sQ=="],

docs/.gitignore

@@ -0,0 +1,3 @@
+node_modules
+.mintlify
+.DS_Store

docs/README.md

@@ -0,0 +1,64 @@
+# Voicebox Documentation
+
+This directory contains the documentation for Voicebox, built with [Mintlify](https://mintlify.com).
+
+## Development
+
+### Prerequisites
+
+Install Mintlify globally using bun:
+
+```bash
+bun add -g mintlify
+```
+
+Or use the helper script:
+
+```bash
+bun run install:mintlify
+```
+
+### Running Locally
+
+```bash
+bun run dev
+```
+
+This will start the Mintlify dev server.
+
+The docs will be available at `http://localhost:3000`
+
+### Structure
+
+```
+docs/
+├── mint.json           # Mintlify configuration
+├── custom.css          # Custom styles
+├── overview/           # Getting started & feature docs
+├── guides/             # User guides
+├── api/                # API reference
+├── development/        # Developer documentation
+├── logo/               # Logo assets
+└── public/             # Static assets
+```
+
+### Writing Docs
+
+- Use `.mdx` files for all documentation pages
+- Follow the existing structure in `mint.json` for navigation
+- Use Mintlify components for enhanced formatting (Card, CardGroup, Accordion, etc.)
+- Reference the [Mintlify documentation](https://mintlify.com/docs) for available components
+
+## Deployment
+
+Docs are automatically deployed when changes are pushed to the main branch.
+
+To manually deploy:
+
+```bash
+mintlify deploy
+```
+
+## Contributing
+
+See [CONTRIBUTING.md](../CONTRIBUTING.md) for contribution guidelines.

docs/TROUBLESHOOTING.md

@@ -90,6 +90,26 @@ chmod +x voicebox-*.AppImage
    - Slower but works without GPU
    - Backend automatically falls back to CPU
 
+### MLX "Failed to load the default metallib" error (Apple Silicon)
+
+**Symptoms:** Generation fails with "library not found" or "metallib" errors
+
+**Solutions:**
+1. **Rebuild server binary**
+   ```bash
+   bun run build:server
+   ```
+   The build script should automatically include MLX Metal shader libraries.
+
+2. **Check MLX installation**
+   ```bash
+   pip install -r backend/requirements-mlx.txt
+   ```
+
+3. **Verify backend detection**
+   - Check server logs for "Backend: MLX"
+   - If showing "Backend: PYTORCH", MLX may not be installed correctly
+
 ### Audio playback issues
 
 **Symptoms:** Generated audio won't play
@@ -111,19 +131,27 @@ chmod +x voicebox-*.AppImage
 **Symptoms:** Generation takes >30 seconds
 
 **Solutions:**
-1. **Use GPU** (if available)
+1. **Check backend type** (Apple Silicon)
+   - Check Settings → Server Status
+   - Should show "Backend: MLX" on Apple Silicon
+   - If showing "Backend: PYTORCH", install MLX: `pip install -r backend/requirements-mlx.txt`
+   - MLX provides 4-5x faster inference on Apple Silicon
+
+2. **Use GPU** (if available)
    - Check Settings → Server Status
    - Should show "GPU available: true"
+   - Apple Silicon: Should show "Metal (Apple Silicon via MLX)"
+   - Windows/Linux: Should show "CUDA" if GPU available
 
-2. **Enable caching**
+3. **Enable caching**
    - Voice prompts are cached automatically
    - Second generation with same voice should be faster
 
-3. **Use smaller model**
+4. **Use smaller model**
    - 0.6B model is faster than 1.7B
    - Quality difference is minimal for most voices
 
-4. **Check system resources**
+5. **Check system resources**
    - Close other CPU/GPU intensive apps
    - Ensure adequate RAM (8GB+ recommended)
 

docs/api/authentication.mdx

@@ -0,0 +1,55 @@
+---
+title: "Authentication"
+description: "API authentication and security"
+---
+
+## Current Status
+
+<Warning>
+  Authentication is not currently implemented in Voicebox. The API is intended for local use only.
+</Warning>
+
+## Local Usage
+
+For local development and usage:
+- API runs on `localhost:17493`
+- No authentication required
+- Access restricted to local machine
+
+## Future Implementation
+
+Authentication will be added in a future release for:
+- Remote deployments
+- Multi-user access
+- Production environments
+
+Planned authentication methods:
+- API keys
+- OAuth 2.0
+- JWT tokens
+
+## Security Best Practices
+
+Until authentication is implemented:
+
+<CardGroup cols={2}>
+  <Card title="Use VPN" icon="shield">
+    Use WireGuard or Tailscale for remote access
+  </Card>
+  <Card title="Reverse Proxy" icon="server">
+    Run behind nginx with basic auth
+  </Card>
+  <Card title="Firewall" icon="fire">
+    Restrict access to trusted IPs only
+  </Card>
+  <Card title="Local Only" icon="laptop">
+    Don't expose to public internet
+  </Card>
+</CardGroup>
+
+## Coming Soon
+
+- API key management
+- User accounts
+- Rate limiting
+- Access control

docs/api/generation.mdx

@@ -0,0 +1,119 @@
+---
+title: "Generation API"
+description: "Generate speech from text"
+---
+
+## Generate Speech
+
+```http
+POST /generate
+```
+
+**Request:**
+```json
+{
+  "text": "Hello world",
+  "profile_id": "abc123",
+  "language": "en"
+}
+```
+
+**Response:**
+```json
+{
+  "id": "gen123",
+  "text": "Hello world",
+  "profile_id": "abc123",
+  "language": "en",
+  "audio_url": "/audio/gen123.wav",
+  "duration": 2.3,
+  "created_at": "2024-01-29T12:00:00Z"
+}
+```
+
+## List History
+
+```http
+GET /history
+```
+
+**Query Parameters:**
+- `profile_id` (optional) - Filter by voice profile
+- `limit` (optional) - Number of results (default: 50)
+- `offset` (optional) - Pagination offset
+
+**Response:**
+```json
+{
+  "generations": [
+    {
+      "id": "gen123",
+      "text": "Hello world",
+      "profile_id": "abc123",
+      "duration": 2.3,
+      "created_at": "2024-01-29T12:00:00Z"
+    }
+  ],
+  "total": 100
+}
+```
+
+## Get Generation
+
+```http
+GET /history/{id}
+```
+
+**Response:**
+```json
+{
+  "id": "gen123",
+  "text": "Hello world",
+  "profile_id": "abc123",
+  "language": "en",
+  "audio_url": "/audio/gen123.wav",
+  "duration": 2.3,
+  "created_at": "2024-01-29T12:00:00Z"
+}
+```
+
+## Delete Generation
+
+```http
+DELETE /history/{id}
+```
+
+**Response:**
+```json
+{
+  "success": true
+}
+```
+
+## TypeScript Example
+
+```typescript
+import { VoiceboxClient } from '@/lib/api'
+
+const client = new VoiceboxClient({
+  baseUrl: 'http://localhost:17493'
+})
+
+// Generate speech
+const generation = await client.generate({
+  text: 'Hello world',
+  profile_id: 'abc123',
+  language: 'en'
+})
+
+// Get audio URL
+const audioUrl = generation.audio_url
+
+// List history
+const history = await client.listHistory({
+  profile_id: 'abc123',
+  limit: 20
+})
+```
+
+For full API documentation, visit `http://localhost:17493/docs` when the server is running.

docs/api/overview.mdx

@@ -0,0 +1,219 @@
+---
+title: "API Overview"
+description: "Integrate voice synthesis into your applications with the Voicebox REST API"
+---
+
+## Introduction
+
+Voicebox exposes a full REST API that allows you to integrate voice synthesis into your own applications. The API runs on `http://localhost:17493` by default.
+
+<Card title="Interactive API Docs" icon="book" href="http://localhost:17493/docs">
+  When Voicebox is running, visit the auto-generated API documentation at `http://localhost:17493/docs`
+</Card>
+
+## Base URL
+
+```
+http://localhost:17493
+```
+
+For remote deployments, replace `localhost` with your server's IP or hostname.
+
+## Authentication
+
+<Note>
+  Currently, the API does not require authentication for local development. Authentication will be added in a future release for production deployments.
+</Note>
+
+## Quick Example
+
+Here's a simple example of generating speech:
+
+```bash
+# Generate speech
+curl -X POST http://localhost:17493/generate \
+  -H "Content-Type: application/json" \
+  -d '{
+    "text": "Hello world",
+    "profile_id": "abc123",
+    "language": "en"
+  }'
+```
+
+## API Endpoints
+
+The Voicebox API is organized into several categories:
+
+<CardGroup cols={2}>
+  <Card title="Voice Profiles" icon="user" href="/api/voice-profiles">
+    Create, list, update, and delete voice profiles
+  </Card>
+  <Card title="Generation" icon="waveform" href="/api/generation">
+    Generate speech from text using voice profiles
+  </Card>
+  <Card title="Recordings" icon="microphone" href="/api/recordings">
+    Record and transcribe audio
+  </Card>
+  <Card title="Stories" icon="film">
+    Create and manage multi-voice stories (coming soon)
+  </Card>
+</CardGroup>
+
+## Core Endpoints
+
+### Voice Profiles
+
+```http
+GET    /profiles              # List all profiles
+POST   /profiles              # Create a new profile
+GET    /profiles/{id}         # Get profile details
+PUT    /profiles/{id}         # Update a profile
+DELETE /profiles/{id}         # Delete a profile
+POST   /profiles/{id}/samples # Add voice sample
+```
+
+### Generation
+
+```http
+POST   /generate              # Generate speech
+GET    /history               # List generation history
+GET    /history/{id}          # Get generation details
+DELETE /history/{id}          # Delete from history
+```
+
+### Recordings
+
+```http
+POST   /recordings            # Start recording
+POST   /recordings/stop       # Stop recording
+POST   /transcribe            # Transcribe audio
+```
+
+## Response Format
+
+All API responses follow a consistent JSON format:
+
+```json
+{
+  "success": true,
+  "data": {
+    // Response data
+  },
+  "error": null
+}
+```
+
+Error responses:
+
+```json
+{
+  "success": false,
+  "data": null,
+  "error": {
+    "message": "Error description",
+    "code": "ERROR_CODE"
+  }
+}
+```
+
+## Data Models
+
+### Voice Profile
+
+```json
+{
+  "id": "abc123",
+  "name": "John Smith",
+  "language": "en",
+  "description": "Professional narrator voice",
+  "created_at": "2024-01-29T12:00:00Z",
+  "samples": [
+    {
+      "id": "sample123",
+      "audio_path": "/path/to/sample.wav",
+      "duration": 15.5
+    }
+  ]
+}
+```
+
+### Generation
+
+```json
+{
+  "id": "gen123",
+  "text": "Hello world",
+  "profile_id": "abc123",
+  "language": "en",
+  "audio_path": "/path/to/output.wav",
+  "duration": 2.3,
+  "created_at": "2024-01-29T12:00:00Z"
+}
+```
+
+## TypeScript Client
+
+Voicebox provides an auto-generated TypeScript client with full type safety:
+
+```typescript
+import { VoiceboxClient } from '@/lib/api'
+
+const client = new VoiceboxClient({
+  baseUrl: 'http://localhost:17493'
+})
+
+// Create a profile
+const profile = await client.createProfile({
+  name: 'John Smith',
+  language: 'en'
+})
+
+// Generate speech
+const generation = await client.generate({
+  text: 'Hello world',
+  profile_id: profile.id,
+  language: 'en'
+})
+```
+
+The client is automatically generated from the OpenAPI schema. See [Development Setup](/development/setup#generate-openapi-client) for details.
+
+## Rate Limiting
+
+<Info>
+  Currently, there are no rate limits for local usage. Rate limiting will be added in a future release for production deployments.
+</Info>
+
+## WebSocket Support
+
+<Note>
+  Real-time streaming generation via WebSockets is planned for a future release.
+</Note>
+
+## Use Cases
+
+<CardGroup cols={2}>
+  <Card title="Game Development" icon="gamepad">
+    Generate dynamic dialogue for NPCs and characters
+  </Card>
+  <Card title="Content Creation" icon="video">
+    Automate voiceovers for videos and podcasts
+  </Card>
+  <Card title="Accessibility" icon="universal-access">
+    Build text-to-speech tools for visually impaired users
+  </Card>
+  <Card title="Voice Assistants" icon="robot">
+    Create custom voice interfaces
+  </Card>
+</CardGroup>
+
+## Next Steps
+
+<CardGroup cols={2}>
+  <Card title="Voice Profiles API" icon="user" href="/api/voice-profiles">
+    Learn how to manage voice profiles
+  </Card>
+  <Card title="Generation API" icon="waveform" href="/api/generation">
+    Generate speech from text
+  </Card>
+</CardGroup>

docs/api/recordings.mdx

@@ -0,0 +1,95 @@
+---
+title: "Recordings API"
+description: "Record and transcribe audio"
+---
+
+## Start Recording
+
+```http
+POST /recordings/start
+```
+
+**Request:**
+```json
+{
+  "source": "microphone"
+}
+```
+
+**Response:**
+```json
+{
+  "recording_id": "rec123",
+  "status": "recording"
+}
+```
+
+## Stop Recording
+
+```http
+POST /recordings/stop
+```
+
+**Request:**
+```json
+{
+  "recording_id": "rec123"
+}
+```
+
+**Response:**
+```json
+{
+  "recording_id": "rec123",
+  "audio_url": "/audio/rec123.wav",
+  "duration": 15.5
+}
+```
+
+## Transcribe Audio
+
+```http
+POST /transcribe
+```
+
+**Request:** (multipart/form-data)
+```
+audio: <file>
+language: "en" (optional)
+```
+
+**Response:**
+```json
+{
+  "text": "Transcribed speech text here",
+  "language": "en",
+  "duration": 15.5,
+  "confidence": 0.95
+}
+```
+
+## TypeScript Example
+
+```typescript
+import { VoiceboxClient } from '@/lib/api'
+
+const client = new VoiceboxClient({
+  baseUrl: 'http://localhost:17493'
+})
+
+// Start recording
+const recording = await client.startRecording({
+  source: 'microphone'
+})
+
+// ... record audio ...
+
+// Stop recording
+const result = await client.stopRecording(recording.id)
+
+// Transcribe
+const transcription = await client.transcribe(audioFile, 'en')
+console.log(transcription.text)
+```
+
+For full API documentation, visit `http://localhost:17493/docs` when the server is running.

docs/api/voice-profiles.mdx

@@ -0,0 +1,149 @@
+---
+title: "Voice Profiles API"
+description: "Manage voice profiles programmatically"
+---
+
+## Endpoints
+
+### List Profiles
+
+```http
+GET /profiles
+```
+
+**Response:**
+```json
+{
+  "profiles": [
+    {
+      "id": "abc123",
+      "name": "John Smith",
+      "language": "en",
+      "description": "Professional narrator",
+      "created_at": "2024-01-29T12:00:00Z",
+      "sample_count": 2
+    }
+  ]
+}
+```
+
+### Get Profile
+
+```http
+GET /profiles/{id}
+```
+
+**Response:**
+```json
+{
+  "id": "abc123",
+  "name": "John Smith",
+  "language": "en",
+  "description": "Professional narrator",
+  "created_at": "2024-01-29T12:00:00Z",
+  "samples": [
+    {
+      "id": "sample123",
+      "duration": 15.5,
+      "created_at": "2024-01-29T12:00:00Z"
+    }
+  ]
+}
+```
+
+### Create Profile
+
+```http
+POST /profiles
+```
+
+**Request:**
+```json
+{
+  "name": "John Smith",
+  "language": "en",
+  "description": "Professional narrator"
+}
+```
+
+**Response:**
+```json
+{
+  "id": "abc123",
+  "name": "John Smith",
+  "language": "en",
+  "description": "Professional narrator",
+  "created_at": "2024-01-29T12:00:00Z"
+}
+```
+
+### Update Profile
+
+```http
+PUT /profiles/{id}
+```
+
+**Request:**
+```json
+{
+  "name": "Updated Name",
+  "description": "Updated description"
+}
+```
+
+### Delete Profile
+
+```http
+DELETE /profiles/{id}
+```
+
+**Response:**
+```json
+{
+  "success": true
+}
+```
+
+### Add Voice Sample
+
+```http
+POST /profiles/{id}/samples
+```
+
+**Request:** (multipart/form-data)
+```
+audio: <file>
+```
+
+**Response:**
+```json
+{
+  "sample_id": "sample123",
+  "duration": 15.5
+}
+```
+
+## TypeScript Example
+
+```typescript
+import { VoiceboxClient } from '@/lib/api'
+
+const client = new VoiceboxClient({
+  baseUrl: 'http://localhost:17493'
+})
+
+// Create profile
+const profile = await client.createProfile({
+  name: 'John Smith',
+  language: 'en',
+  description: 'Professional narrator'
+})
+
+// Add sample
+await client.addSample(profile.id, audioFile)
+
+// List all profiles
+const profiles = await client.listProfiles()
+```
+
+For full API documentation, visit `http://localhost:17493/docs` when the server is running.

docs/custom.css

@@ -0,0 +1,15 @@
+/* Anchor hover styles */
+.nav-anchor:hover {
+	@apply text-[#BF9E40];
+}
+
+/* Icon wrapper on hover */
+.nav-anchor:hover div {
+	background: #BF9E40 !important;
+	filter: brightness(1) !important;
+}
+
+/* Icon SVG on hover */
+.nav-anchor:hover svg {
+	@apply bg-white !important;
+}

docs/developer/architecture.mdx

@@ -0,0 +1,206 @@
+---
+title: "Architecture"
+description: "Understanding Voicebox's technical architecture"
+---
+
+## System Overview
+
+Voicebox uses a client-server architecture with a React frontend and Python backend. The desktop app is built with Tauri and contains two main layers:
+
+**Frontend Layer:** A React application that handles the UI components, state management with Zustand, and data fetching with React Query (TanStack Query).
+
+**Backend Layer:** A Python FastAPI server that provides the REST API, runs the TTS engine (Qwen3-TTS), manages the SQLite database, and handles audio processing.
+
+These two layers communicate via HTTP, with the frontend making API requests to the backend.
+
+## Frontend Architecture
+
+### Tech Stack
+
+- **Framework**: React 18 with TypeScript
+- **State Management**: Zustand stores
+- **Data Fetching**: React Query (TanStack Query)
+- **Styling**: Tailwind CSS
+- **Audio**: WaveSurfer.js
+- **Desktop**: Tauri (Rust)
+
+### Component Structure
+
+```
+app/src/
+├── components/       # React components
+│   ├── profiles/    # Voice profile UI
+│   ├── generation/  # Speech generation UI
+│   ├── stories/     # Timeline editor
+│   └── shared/      # Reusable components
+├── lib/             # Utilities
+│   ├── api/         # Generated API client
+│   └── utils/       # Helper functions
+├── hooks/           # React hooks
+└── stores/          # Zustand state stores
+```
+
+### State Management
+
+```typescript
+// Example: Profile store
+const useProfileStore = create((set) => ({
+  profiles: [],
+  selectedProfile: null,
+  setProfiles: (profiles) => set({ profiles }),
+  selectProfile: (id) => set({ selectedProfile: id })
+}))
+```
+
+## Backend Architecture
+
+### Tech Stack
+
+- **Framework**: FastAPI (Python 3.11+)
+- **TTS Model**: Qwen3-TTS
+- **Transcription**: Whisper
+- **Database**: SQLite
+- **Audio**: librosa, soundfile
+
+### API Structure
+
+```python
+# main.py - API routes
+@app.post("/generate")
+async def generate_speech(request: GenerateRequest):
+    # 1. Validate request
+    # 2. Load voice profile
+    # 3. Generate audio with TTS
+    # 4. Save to database
+    # 5. Return response
+```
+
+### Data Model
+
+The database uses three main tables:
+
+**Profile Table:** Stores voice profiles with fields for id, name, and language.
+
+**Sample Table:** Stores audio samples linked to profiles via profile_id, with fields for audio_path and duration.
+
+**Generation Table:** Stores generated audio with fields for id, profile_id, text, and audio_path.
+
+## Desktop App (Tauri)
+
+### Rust Backend
+
+```rust
+// Sidecar process management
+// File system access
+// Native integrations
+```
+
+### Responsibilities
+
+- Launch Python backend as sidecar process
+- Native file dialogs
+- System tray integration
+- Auto-updates
+- OS-specific features
+
+## Build Process
+
+### Development
+
+```bash
+# Frontend (Vite dev server)
+cd app && bun run dev
+
+# Backend (manual start)
+cd backend && uvicorn main:app --reload
+
+# Desktop app (connects to manual backend)
+bun run dev
+```
+
+### Production
+
+```bash
+# Build everything (server binary + Tauri app)
+bun run build
+
+# Or build separately:
+# 1. Build server binary (PyInstaller)
+bun run build:server
+
+# 2. Build Tauri app (includes server)
+cd tauri && bun run tauri build
+```
+
+## Data Flow
+
+### Generation Flow
+
+When a user generates speech, the data flows through the following stages:
+
+1. **User Input** - User enters text in a React component
+2. **State Update** - Text is stored in Zustand state
+3. **API Request** - React Query mutation triggers an API call via fetch
+4. **Backend Processing** - FastAPI endpoint receives the request
+5. **TTS Generation** - Qwen3-TTS model generates the audio
+6. **Storage** - Audio file is saved to disk and a database record is created
+7. **Response** - Backend returns the audio URL
+8. **Cache Update** - React Query updates its cache with the response
+9. **UI Update** - Component re-renders with new data
+10. **Playback** - User can play the generated audio
+
+## Performance Considerations
+
+### Frontend
+
+- **Code splitting** - Lazy load routes
+- **Memoization** - React.memo for heavy components
+- **Virtual scrolling** - For large lists
+- **Debouncing** - Search and input handling
+
+### Backend
+
+- **Async operations** - All I/O is async
+- **Model caching** - Keep TTS model in memory
+- **Voice prompt caching** - Reuse embeddings
+- **Connection pooling** - Database connections
+
+## Security
+
+### Current
+
+- Local-only by default
+- No authentication (localhost trust)
+- File system sandboxing via Tauri
+
+### Planned
+
+- API key authentication
+- User accounts
+- Rate limiting
+- HTTPS support
+
+## Deployment Modes
+
+### Local Mode
+
+- Backend runs as sidecar
+- All data stays on device
+- No network required
+
+### Remote Mode
+
+- Backend on separate machine
+- Frontend connects via HTTP
+- Shared infrastructure possible
+
+## Next Steps
+
+<CardGroup cols={2}>
+  <Card title="Development Setup" icon="code" href="/development/setup">
+    Set up your dev environment
+  </Card>
+  <Card title="Contributing" icon="code-pull-request" href="/development/contributing">
+    Contribute to Voicebox
+  </Card>
+</CardGroup>