merge: resolve conflicts with latest main

Merge pull request #257 from jamiepine/feat/chatterbox
feat: Chatterbox TTS engine with multilingual voice cloning
2026-09-26 21:55:15 -07:00 · 2026-03-13 02:41:28 -07:00 · 2026-03-13 02:12:56 -07:00 · 2026-03-13 02:09:32 -07:00 · 2026-03-13 02:09:32 -07:00 · 2026-03-13 02:09:32 -07:00
39 changed files with 4234 additions and 567 deletions
@@ -5,6 +5,14 @@ All notable changes to Voicebox will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

+## [Unreleased]
+
+### Fixed
+- **Profile Name Validation** - Added proper validation to prevent duplicate profile names ([#134](https://github.com/jamiepine/voicebox/issues/134))
+  - Users now receive clear error messages when attempting to create or update profiles with duplicate names
+  - Improved error handling in create and update profile API endpoints
+  - Added comprehensive test suite for duplicate name validation
+
 ## [0.1.0] - 2026-01-25

 ### Added
@@ -55,6 +63,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ### Fixed
 - Audio export failing when Tauri save dialog returns object instead of string path
+- OpenAPI client generator script now documents the local backend port and avoids an unused loop variable warning

 ### Added
 - **Makefile** - Comprehensive development workflow automation with commands for setup, development, building, testing, and code quality checks
@@ -62,9 +71,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
  - Self-documenting help system with `make help`
  - Colored output for better readability
  - Supports parallel development server execution
+- **Audiobook Tab** - New long-form narration workflow in the app
+  - Import/paste `.txt` book content and review/edit before generation
+  - Generate a quick 5-sentence preview before full run
+  - Chunk long text automatically and process chunk-by-chunk with retry support
+  - Auto-create and update a Story during generation, with export shortcut
+- **Text chunking utility** - Added reusable sentence-aware chunking for large text inputs (`app/src/lib/utils/textChunking.ts`)

 ### Changed
 - **README** - Added Makefile reference and updated Quick Start with Makefile-based setup instructions alongside manual setup
+- **Navigation** - Added Audiobook route/tab to the app sidebar
+- **Generation API types** - Added optional `instruct` field to `GenerationRequest`
+- **App styling** - Added `scrollbar-visible` utility styles for long-scroll panels/editors

 ---

@@ -32,7 +32,26 @@ 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.
+**Using `just` (recommended):**
+
+Install [just](https://github.com/casey/just) (`brew install just` or `cargo install just`), then:
+
+```bash
+just setup   # creates venv, installs Python + JS deps
+just dev     # starts backend + desktop app in one terminal
+```
+
+Other useful commands:
+
+```bash
+just dev-web       # backend + web app (no Tauri/Rust build)
+just dev-backend   # backend only
+just kill          # stop all dev processes
+just clean-all     # nuke everything and start fresh
+just --list        # see all available commands
+```
+
+**Using the Makefile:** Run `make setup` then `make dev`. See `make help` for all commands.

 **Manual setup (required for Windows):**

@@ -407,7 +426,7 @@ See [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md) for common issues and sol

 - **Backend won't start:** Check Python version (3.11+), ensure venv is activated, install dependencies
 - **Tauri build fails:** Ensure Rust is installed, clean build with `cd tauri/src-tauri && cargo clean`
- **OpenAPI client generation fails:** Ensure backend is running, check `curl http://localhost:8000/openapi.json`
+- **OpenAPI client generation fails:** Ensure backend is running, check `curl http://localhost:17493/openapi.json`

 ## Questions?

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

 dev-backend: ## Start FastAPI backend server
@@ -147,17 +147,20 @@ Create multi-voice narratives, podcasts, and conversations with a timeline-based

 Voicebox exposes a full REST API, so you can integrate voice synthesis into your own apps.

+For the current local app and development workflow, the backend is typically available at `http://localhost:17493`.
+If you launch the backend manually with a different host or port, use that address instead.
+
 ```bash
 # Generate speech
-curl -X POST http://localhost:8000/generate \
+curl -X POST http://localhost:17493/generate \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello world", "profile_id": "abc123", "language": "en"}'

 # List voice profiles
-curl http://localhost:8000/profiles
+curl http://localhost:17493/profiles

 # Create a profile
-curl -X POST http://localhost:8000/profiles \
+curl -X POST http://localhost:17493/profiles \
  -H "Content-Type: application/json" \
  -d '{"name": "My Voice", "language": "en"}'
 ```
@@ -170,7 +173,7 @@ curl -X POST http://localhost:8000/profiles \
 - Voice assistants
 - Content creation automation

-Full API documentation available at `http://localhost:8000/docs` when running.
+Full API documentation is available at `http://localhost:17493/docs` in the default local workflow, or at `/docs` on whatever server address you configured.

 ---

@@ -225,42 +228,21 @@ Voicebox aims to be the **one-stop shop for everything voice** — cloning, synt

 See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed setup and contribution guidelines.

-**Using the Makefile (recommended):** Run `make help` to see all available commands for setup, development, building, and testing.
-
 ### Quick Start

-**With Makefile (Unix/macOS/Linux):**
-
 ```bash
-# Clone the repo
 git clone https://github.com/jamiepine/voicebox.git
 cd voicebox

-# Setup everything
-make setup
-
-# Start development
-make dev
+just setup   # creates Python venv, installs all deps
+just dev     # starts backend + desktop app
 ```

-**Manual setup (all platforms):**
+Install [just](https://github.com/casey/just): `brew install just` or `cargo install just`. Run `just --list` to see all commands.

-```bash
-# Clone the repo
-git clone https://github.com/jamiepine/voicebox.git
-cd voicebox
+Also available via Makefile: `make setup && make dev` (run `make help` for all commands).

-# Install dependencies
-bun install
-
-# Install Python dependencies
-cd backend && pip install -r requirements.txt && cd ..
-
-# Start development
-bun run dev
-```
-
-**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org). [XCode on macOS](https://developer.apple.com/xcode/).
+**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org), [XCode on macOS](https://developer.apple.com/xcode/).

 **Performance:** 
 - **Apple Silicon (M1/M2/M3)**: Uses MLX backend with native Metal acceleration for 4-5x faster inference
@@ -316,7 +316,7 @@ export function FloatingGenerateBox({
                  </span>
                </div>
                <AnimatePresence>
-                  {isExpanded && (
+                  {isExpanded && form.watch('engine') === 'qwen' && (
                    <motion.div
                      initial={{ opacity: 0, scale: 0.8 }}
                      animate={{ opacity: 1, scale: 1 }}
@@ -402,30 +402,48 @@ export function FloatingGenerateBox({
                    )}
                  />

-                  <FormField
-                    control={form.control}
-                    name="modelSize"
-                    render={({ field }) => (
-                      <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">
-                              <SelectValue />
-                            </SelectTrigger>
-                          </FormControl>
-                          <SelectContent>
-                            <SelectItem value="1.7B" className="text-xs text-muted-foreground">
-                              Qwen3-TTS 1.7B
-                            </SelectItem>
-                            <SelectItem value="0.6B" className="text-xs text-muted-foreground">
-                              Qwen3-TTS 0.6B
-                            </SelectItem>
-                          </SelectContent>
-                        </Select>
-                        <FormMessage className="text-xs" />
-                      </FormItem>
-                    )}
-                  />
+                  <FormItem className="flex-1 space-y-0">
+                    <Select
+                      value={
+                        form.watch('engine') === 'luxtts'
+                          ? 'luxtts'
+                          : form.watch('engine') === 'chatterbox'
+                            ? 'chatterbox'
+                            : `qwen:${form.watch('modelSize') || '1.7B'}`
+                      }
+                      onValueChange={(value) => {
+                        if (value === 'luxtts') {
+                          form.setValue('engine', 'luxtts');
+                        } else if (value === 'chatterbox') {
+                          form.setValue('engine', 'chatterbox');
+                        } else {
+                          const [, modelSize] = value.split(':');
+                          form.setValue('engine', 'qwen');
+                          form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
+                        }
+                      }}
+                    >
+                      <FormControl>
+                        <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
+                          <SelectValue />
+                        </SelectTrigger>
+                      </FormControl>
+                      <SelectContent>
+                        <SelectItem value="qwen:1.7B" className="text-xs text-muted-foreground">
+                          Qwen3-TTS 1.7B
+                        </SelectItem>
+                        <SelectItem value="qwen:0.6B" className="text-xs text-muted-foreground">
+                          Qwen3-TTS 0.6B
+                        </SelectItem>
+                        <SelectItem value="luxtts" className="text-xs text-muted-foreground">
+                          LuxTTS
+                        </SelectItem>
+                        <SelectItem value="chatterbox" className="text-xs text-muted-foreground">
+                          Chatterbox
+                        </SelectItem>
+                      </SelectContent>
+                    </Select>
+                  </FormItem>
                </div>
              </motion.div>
            </AnimatePresence>
@@ -76,29 +76,74 @@ export function GenerationForm() {
              )}
            />

-            <FormField
-              control={form.control}
-              name="instruct"
-              render={({ field }) => (
-                <FormItem>
-                  <FormLabel>Delivery Instructions (optional)</FormLabel>
-                  <FormControl>
-                    <Textarea
-                      placeholder="e.g. Speak slowly with emphasis, Warm and friendly tone, Professional and authoritative..."
-                      className="min-h-[80px]"
-                      {...field}
-                    />
-                  </FormControl>
-                  <FormDescription>
-                    Natural language instructions to control speech delivery (tone, emotion, pace).
-                    Max 500 characters
-                  </FormDescription>
-                  <FormMessage />
-                </FormItem>
-              )}
-            />
+            {form.watch('engine') === 'qwen' && (
+              <FormField
+                control={form.control}
+                name="instruct"
+                render={({ field }) => (
+                  <FormItem>
+                    <FormLabel>Delivery Instructions (optional)</FormLabel>
+                    <FormControl>
+                      <Textarea
+                        placeholder="e.g. Speak slowly with emphasis, Warm and friendly tone, Professional and authoritative..."
+                        className="min-h-[80px]"
+                        {...field}
+                      />
+                    </FormControl>
+                    <FormDescription>
+                      Natural language instructions to control speech delivery (tone, emotion,
+                      pace). Max 500 characters
+                    </FormDescription>
+                    <FormMessage />
+                  </FormItem>
+                )}
+              />
+            )}

            <div className="grid gap-4 md:grid-cols-3">
+              <FormItem>
+                <FormLabel>Model</FormLabel>
+                <Select
+                  value={
+                    form.watch('engine') === 'luxtts'
+                      ? 'luxtts'
+                      : form.watch('engine') === 'chatterbox'
+                        ? 'chatterbox'
+                        : `qwen:${form.watch('modelSize') || '1.7B'}`
+                  }
+                  onValueChange={(value) => {
+                    if (value === 'luxtts') {
+                      form.setValue('engine', 'luxtts');
+                    } else if (value === 'chatterbox') {
+                      form.setValue('engine', 'chatterbox');
+                    } else {
+                      const [, modelSize] = value.split(':');
+                      form.setValue('engine', 'qwen');
+                      form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
+                    }
+                  }}
+                >
+                  <FormControl>
+                    <SelectTrigger>
+                      <SelectValue />
+                    </SelectTrigger>
+                  </FormControl>
+                  <SelectContent>
+                    <SelectItem value="qwen:1.7B">Qwen3-TTS 1.7B</SelectItem>
+                    <SelectItem value="qwen:0.6B">Qwen3-TTS 0.6B</SelectItem>
+                    <SelectItem value="luxtts">LuxTTS</SelectItem>
+                    <SelectItem value="chatterbox">Chatterbox</SelectItem>
+                  </SelectContent>
+                </Select>
+                <FormDescription>
+                  {form.watch('engine') === 'luxtts'
+                    ? 'Fast, English-focused'
+                    : form.watch('engine') === 'chatterbox'
+                      ? 'Multilingual, incl. Hebrew'
+                      : 'Multi-language, two sizes'}
+                </FormDescription>
+              </FormItem>
+
              <FormField
                control={form.control}
                name="language"
@@ -124,29 +169,6 @@ export function GenerationForm() {
                )}
              />

-              <FormField
-                control={form.control}
-                name="modelSize"
-                render={({ field }) => (
-                  <FormItem>
-                    <FormLabel>Model Size</FormLabel>
-                    <Select onValueChange={field.onChange} defaultValue={field.value}>
-                      <FormControl>
-                        <SelectTrigger>
-                          <SelectValue />
-                        </SelectTrigger>
-                      </FormControl>
-                      <SelectContent>
-                        <SelectItem value="1.7B">Qwen TTS 1.7B (Higher Quality)</SelectItem>
-                        <SelectItem value="0.6B">Qwen TTS 0.6B (Faster)</SelectItem>
-                      </SelectContent>
-                    </Select>
-                    <FormDescription>Larger models produce better quality</FormDescription>
-                    <FormMessage />
-                  </FormItem>
-                )}
-              />
-
              <FormField
                control={form.control}
                name="seed"
@@ -170,11 +192,7 @@ export function GenerationForm() {
              />
            </div>

-            <Button
-              type="submit"
-              className="w-full"
-              disabled={isPending || !selectedProfileId}
-            >
+            <Button type="submit" className="w-full" disabled={isPending || !selectedProfileId}>
              {isPending ? (
                <>
                  <Loader2 className="mr-2 h-4 w-4 animate-spin" />
@@ -2,7 +2,7 @@ import { ModelManagement } from '@/components/ServerSettings/ModelManagement';

 export function ModelsTab() {
  return (
-    <div className="space-y-4 overflow-y-auto flex flex-col">
+    <div className="h-full flex flex-col p-4">
      <ModelManagement />
    </div>
  );
@@ -32,7 +32,7 @@ export function GpuAcceleration() {
  } = useQuery({
    queryKey: ['cuda-status', serverUrl],
    queryFn: () => apiClient.getCudaStatus(),
-    refetchInterval: cudaStatusLoading ? false : 10000,
+    refetchInterval: (query) => (query.state.status === 'pending' ? false : 10000),
    retry: 1,
    enabled: !!health, // Only fetch when backend is reachable
  });
@@ -1,6 +1,21 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
-import { ChevronDown, ChevronUp, Download, Loader2, RotateCcw, Trash2, X } from 'lucide-react';
-import { useCallback, useState } from 'react';
+import {
+  ChevronDown,
+  ChevronRight,
+  ChevronUp,
+  CircleCheck,
+  CircleX,
+  Download,
+  ExternalLink,
+  HardDrive,
+  Heart,
+  Loader2,
+  RotateCcw,
+  Scale,
+  Trash2,
+  X,
+} from 'lucide-react';
+import { useCallback, useMemo, useState } from 'react';
 import {
  AlertDialog,
  AlertDialogAction,
@@ -13,12 +28,59 @@ import {
 } from '@/components/ui/alert-dialog';
 import { Badge } from '@/components/ui/badge';
 import { Button } from '@/components/ui/button';
-import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card';
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogHeader,
+  DialogTitle,
+} from '@/components/ui/dialog';
+import { Progress } from '@/components/ui/progress';
 import { useToast } from '@/components/ui/use-toast';
 import { apiClient } from '@/lib/api/client';
-import type { ActiveDownloadTask } from '@/lib/api/types';
+import type { ActiveDownloadTask, HuggingFaceModelInfo, ModelStatus } from '@/lib/api/types';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';

+async function fetchHuggingFaceModelInfo(repoId: string): Promise<HuggingFaceModelInfo> {
+  const response = await fetch(`https://huggingface.co/api/models/${repoId}`);
+  if (!response.ok) throw new Error(`Failed to fetch model info: ${response.status}`);
+  return response.json();
+}
+
+function formatDownloads(n: number): string {
+  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;
+  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}k`;
+  return n.toString();
+}
+
+function formatLicense(license: string): string {
+  const map: Record<string, string> = {
+    'apache-2.0': 'Apache 2.0',
+    mit: 'MIT',
+    'cc-by-4.0': 'CC BY 4.0',
+    'cc-by-sa-4.0': 'CC BY-SA 4.0',
+    'cc-by-nc-4.0': 'CC BY-NC 4.0',
+    'openrail++': 'OpenRAIL++',
+    openrail: 'OpenRAIL',
+  };
+  return map[license] || license;
+}
+
+function formatPipelineTag(tag: string): string {
+  return tag
+    .split('-')
+    .map((w) => w.charAt(0).toUpperCase() + w.slice(1))
+    .join(' ');
+}
+
+function formatBytes(bytes: number): string {
+  if (bytes === 0) return '0 B';
+  const k = 1024;
+  const sizes = ['B', 'KB', 'MB', 'GB'];
+  const i = Math.floor(Math.log(bytes) / Math.log(k));
+  return `${(bytes / k ** i).toFixed(1)} ${sizes[i]}`;
+}
+
 export function ModelManagement() {
  const { toast } = useToast();
  const queryClient = useQueryClient();
@@ -28,36 +90,48 @@ export function ModelManagement() {
  const [dismissedErrors, setDismissedErrors] = useState<Set<string>>(new Set());
  const [localErrors, setLocalErrors] = useState<Map<string, string>>(new Map());

+  // Modal state
+  const [selectedModel, setSelectedModel] = useState<ModelStatus | null>(null);
+  const [detailOpen, setDetailOpen] = useState(false);
+
  const { data: modelStatus, isLoading } = useQuery({
    queryKey: ['modelStatus'],
    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
+    refetchInterval: 5000,
  });

  const { data: activeTasks } = useQuery({
    queryKey: ['activeTasks'],
    queryFn: () => apiClient.getActiveTasks(),
-    refetchInterval: 5000,
+    refetchInterval: (query) => {
+      const data = query.state.data;
+      const hasActive = data?.downloads.some((d) => d.status === 'downloading');
+      return hasActive ? 1000 : 5000;
+    },
+  });
+
+  // HuggingFace model card query - only fetches when modal is open and model has a repo ID
+  const { data: hfModelInfo, isLoading: hfLoading } = useQuery({
+    queryKey: ['hfModelInfo', selectedModel?.hf_repo_id],
+    queryFn: () => fetchHuggingFaceModelInfo(selectedModel!.hf_repo_id!),
+    enabled: detailOpen && !!selectedModel?.hf_repo_id,
+    staleTime: 1000 * 60 * 30, // Cache for 30 minutes
+    retry: 1,
  });

  // Build a map of errored downloads for quick lookup, excluding dismissed ones
-  // Merge server errors with locally captured SSE errors
  const erroredDownloads = new Map<string, ActiveDownloadTask>();
  if (activeTasks?.downloads) {
    for (const dl of activeTasks.downloads) {
      if (dl.status === 'error' && !dismissedErrors.has(dl.model_name)) {
-        // Prefer locally captured error (from SSE) over server error
        const localErr = localErrors.get(dl.model_name);
        erroredDownloads.set(dl.model_name, localErr ? { ...dl, error: localErr } : dl);
      }
    }
  }
-  // Also add locally captured errors that aren't in server response yet
  for (const [modelName, error] of localErrors) {
    if (!erroredDownloads.has(modelName) && !dismissedErrors.has(modelName)) {
      erroredDownloads.set(modelName, {
@@ -71,27 +145,39 @@ export function ModelManagement() {

  const errorCount = erroredDownloads.size;

-  // Callbacks for download completion
+  // Build progress map from active tasks for inline display
+  const downloadProgressMap = useMemo(() => {
+    const map = new Map<string, ActiveDownloadTask>();
+    if (activeTasks?.downloads) {
+      for (const dl of activeTasks.downloads) {
+        if (dl.status === 'downloading') {
+          map.set(dl.model_name, dl);
+        }
+      }
+    }
+    return map;
+  }, [activeTasks]);
+
  const handleDownloadComplete = useCallback(() => {
-    console.log('[ModelManagement] Download complete, clearing state');
    setDownloadingModel(null);
    setDownloadingDisplayName(null);
    queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
    queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
  }, [queryClient]);

-  const handleDownloadError = useCallback((error: string) => {
-    console.log('[ModelManagement] Download error, clearing state');
-    if (downloadingModel) {
-      setLocalErrors((prev) => new Map(prev).set(downloadingModel, error));
-      setConsoleOpen(true);
-    }
-    setDownloadingModel(null);
-    setDownloadingDisplayName(null);
-    queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
-  }, [queryClient, downloadingModel]);
+  const handleDownloadError = useCallback(
+    (error: string) => {
+      if (downloadingModel) {
+        setLocalErrors((prev) => new Map(prev).set(downloadingModel, error));
+        setConsoleOpen(true);
+      }
+      setDownloadingModel(null);
+      setDownloadingDisplayName(null);
+      queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
+    },
+    [queryClient, downloadingModel],
+  );

-  // Use progress toast hook for the downloading model
  useModelDownloadToast({
    modelName: downloadingModel || '',
    displayName: downloadingDisplayName || '',
@@ -108,36 +194,24 @@ export function ModelManagement() {
  } | null>(null);

  const handleDownload = async (modelName: string) => {
-    console.log('[Download] Button clicked for:', modelName, 'at', new Date().toISOString());
-    // Clear any previous dismissal so fresh errors can appear
    setDismissedErrors((prev) => {
      const next = new Set(prev);
      next.delete(modelName);
      return next;
    });

-    // 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);
+      await apiClient.triggerModelDownload(modelName);

-      // NOW set state to enable SSE tracking (after download has started on backend)
      setDownloadingModel(modelName);
      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'] });
      queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
    } catch (error) {
-      console.error('[Download] Download failed:', error);
      setDownloadingModel(null);
      setDownloadingDisplayName(null);
      toast({
@@ -157,15 +231,17 @@ export function ModelManagement() {
  });

  const handleCancel = (modelName: string) => {
-    // Snapshot previous state for rollback
    const prevDismissed = dismissedErrors;
    const prevLocalErrors = localErrors;
    const prevDownloadingModel = downloadingModel;
    const prevDownloadingDisplayName = downloadingDisplayName;

-    // Optimistically hide the error and suppress downloading state in UI
    setDismissedErrors((prev) => new Set(prev).add(modelName));
-    setLocalErrors((prev) => { const next = new Map(prev); next.delete(modelName); return next; });
+    setLocalErrors((prev) => {
+      const next = new Map(prev);
+      next.delete(modelName);
+      return next;
+    });
    if (downloadingModel === modelName) {
      setDownloadingModel(null);
      setDownloadingDisplayName(null);
@@ -173,12 +249,15 @@ export function ModelManagement() {

    cancelMutation.mutate(modelName, {
      onError: () => {
-        // Rollback optimistic updates on failure
        setDismissedErrors(prevDismissed);
        setLocalErrors(prevLocalErrors);
        setDownloadingModel(prevDownloadingModel);
        setDownloadingDisplayName(prevDownloadingDisplayName);
-        toast({ title: 'Cancel failed', description: 'Could not cancel the download task.', variant: 'destructive' });
+        toast({
+          title: 'Cancel failed',
+          description: 'Could not cancel the download task.',
+          variant: 'destructive',
+        });
      },
    });
  };
@@ -197,30 +276,22 @@ export function ModelManagement() {

  const deleteMutation = useMutation({
    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');
+    onSuccess: async () => {
      toast({
        title: 'Model deleted',
        description: `${modelToDelete?.displayName || 'Model'} has been deleted successfully.`,
      });
      setDeleteDialogOpen(false);
      setModelToDelete(null);
-      console.log('[Delete] Invalidating modelStatus query');
-      await queryClient.invalidateQueries({
-        queryKey: ['modelStatus'],
-        refetchType: 'all',
-      });
-      console.log('[Delete] Explicitly refetching modelStatus query');
+      setDetailOpen(false);
+      setSelectedModel(null);
+      await queryClient.invalidateQueries({ queryKey: ['modelStatus'], refetchType: 'all' });
      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,
@@ -230,149 +301,438 @@ export function ModelManagement() {
  });

  const formatSize = (sizeMb?: number): string => {
-    if (!sizeMb) return 'Unknown';
+    if (!sizeMb) return 'Unknown size';
    if (sizeMb < 1024) return `${sizeMb.toFixed(1)} MB`;
    return `${(sizeMb / 1024).toFixed(2)} GB`;
  };

+  const getModelState = (model: ModelStatus) => {
+    const isDownloading =
+      (model.downloading || downloadingModel === model.model_name) &&
+      !erroredDownloads.has(model.model_name) &&
+      !dismissedErrors.has(model.model_name);
+    const hasError = erroredDownloads.has(model.model_name);
+    return { isDownloading, hasError };
+  };
+
+  const openModelDetail = (model: ModelStatus) => {
+    setSelectedModel(model);
+    setDetailOpen(true);
+  };
+
+  const ttsModels = modelStatus?.models.filter((m) => m.model_name.startsWith('qwen-tts')) ?? [];
+  const otherTtsModels =
+    modelStatus?.models.filter(
+      (m) => m.model_name.startsWith('luxtts') || m.model_name.startsWith('chatterbox'),
+    ) ?? [];
+  const whisperModels = modelStatus?.models.filter((m) => m.model_name.startsWith('whisper')) ?? [];
+
+  // Build sections
+  const sections: { label: string; models: ModelStatus[] }[] = [
+    { label: 'Voice Generation', models: ttsModels },
+    ...(otherTtsModels.length > 0 ? [{ label: 'Other Voice Models', models: otherTtsModels }] : []),
+    { label: 'Transcription', models: whisperModels },
+  ];
+
+  // Get detail modal state for selected model
+  const selectedState = selectedModel ? getModelState(selectedModel) : null;
+  const selectedError = selectedModel ? erroredDownloads.get(selectedModel.model_name) : undefined;
+
+  // Keep selectedModel data fresh from query results
+  const freshSelectedModel =
+    selectedModel && modelStatus
+      ? modelStatus.models.find((m) => m.model_name === selectedModel.model_name) || selectedModel
+      : selectedModel;
+
+  // Derive license from HF data
+  const license =
+    hfModelInfo?.cardData?.license ||
+    hfModelInfo?.tags?.find((t) => t.startsWith('license:'))?.replace('license:', '');
+
  return (
-    <Card>
-      <CardHeader>
-        <CardTitle>Model Management</CardTitle>
-        <CardDescription>
+    <div className="flex flex-col h-full">
+      {/* Header */}
+      <div className="shrink-0 pb-4">
+        <h1 className="text-lg font-semibold">Models</h1>
+        <p className="text-sm text-muted-foreground">
          Download and manage AI models for voice generation and transcription
-        </CardDescription>
-      </CardHeader>
-      <CardContent className="space-y-4">
-        {isLoading ? (
-          <div className="flex items-center justify-center py-8">
-            <Loader2 className="h-6 w-6 animate-spin text-muted-foreground" />
-          </div>
-        ) : modelStatus ? (
-          <div className="space-y-4">
-            {/* TTS Models */}
-            <div>
-              <h3 className="text-sm font-semibold mb-3 text-muted-foreground">
-                Voice Generation Models
-              </h3>
-              <div className="space-y-2">
-                {modelStatus.models
-                  .filter((m) => m.model_name.startsWith('qwen-tts'))
-                  .map((model) => (
-                    <ModelItem
-                      key={model.model_name}
-                      model={model}
-                      onDownload={() => handleDownload(model.model_name)}
-                      onDelete={() => {
-                        setModelToDelete({
-                          name: model.model_name,
-                          displayName: model.display_name,
-                          sizeMb: model.size_mb,
-                        });
-                        setDeleteDialogOpen(true);
-                      }}
-                      onCancel={() => handleCancel(model.model_name)}
-                      isDownloading={downloadingModel === model.model_name}
-                      isCancelling={cancelMutation.isPending && cancelMutation.variables === model.model_name}
-                      isDismissed={dismissedErrors.has(model.model_name)}
-                      erroredDownload={erroredDownloads.get(model.model_name)}
-                      formatSize={formatSize}
-                    />
-                  ))}
-              </div>
-            </div>
+        </p>
+      </div>

-            {/* Whisper Models */}
-            <div>
-              <h3 className="text-sm font-semibold mb-3 text-muted-foreground">
-                Transcription Models
-              </h3>
-              <div className="space-y-2">
-                {modelStatus.models
-                  .filter((m) => m.model_name.startsWith('whisper'))
-                  .map((model) => (
-                    <ModelItem
+      {/* Model list */}
+      {isLoading ? (
+        <div className="flex items-center justify-center py-16">
+          <Loader2 className="h-5 w-5 animate-spin text-muted-foreground" />
+        </div>
+      ) : modelStatus ? (
+        <div className="flex-1 min-h-0 overflow-y-auto space-y-6">
+          {sections.map((section) => (
+            <div key={section.label}>
+              <h2 className="text-xs font-medium text-muted-foreground uppercase tracking-wider mb-1 px-1">
+                {section.label}
+              </h2>
+              <div className="border rounded-lg divide-y overflow-hidden">
+                {section.models.map((model) => {
+                  const { isDownloading, hasError } = getModelState(model);
+                  return (
+                    <button
                      key={model.model_name}
-                      model={model}
-                      onDownload={() => handleDownload(model.model_name)}
-                      onDelete={() => {
-                        setModelToDelete({
-                          name: model.model_name,
-                          displayName: model.display_name,
-                          sizeMb: model.size_mb,
-                        });
-                        setDeleteDialogOpen(true);
-                      }}
-                      onCancel={() => handleCancel(model.model_name)}
-                      isDownloading={downloadingModel === model.model_name}
-                      isCancelling={cancelMutation.isPending && cancelMutation.variables === model.model_name}
-                      isDismissed={dismissedErrors.has(model.model_name)}
-                      erroredDownload={erroredDownloads.get(model.model_name)}
-                      formatSize={formatSize}
-                    />
-                  ))}
-              </div>
-            </div>
-
-            {/* Console Panel */}
-            {errorCount > 0 && (
-              <div className="border rounded-lg overflow-hidden">
-                <div className="flex items-center justify-between px-3 py-1.5 bg-muted/50 text-xs font-medium text-muted-foreground">
-                  <button
-                    type="button"
-                    onClick={() => setConsoleOpen((v) => !v)}
-                    className="flex items-center gap-2 hover:text-foreground transition-colors"
-                  >
-                    {consoleOpen ? (
-                      <ChevronUp className="h-3.5 w-3.5" />
-                    ) : (
-                      <ChevronDown className="h-3.5 w-3.5" />
-                    )}
-                    <span>Problems</span>
-                    <Badge variant="destructive" className="text-[10px] h-4 px-1.5 rounded-full">
-                      {errorCount}
-                    </Badge>
-                  </button>
-                  <Button
-                    size="sm"
-                    variant="ghost"
-                    className="h-6 px-2 text-xs text-muted-foreground hover:text-foreground"
-                    onClick={() => clearAllMutation.mutate()}
-                    disabled={clearAllMutation.isPending}
-                  >
-                    <RotateCcw className="h-3 w-3 mr-1" />
-                    Clear All
-                  </Button>
-                </div>
-                {consoleOpen && (
-                  <div className="bg-[#1e1e1e] text-[#d4d4d4] p-3 max-h-48 overflow-auto font-mono text-xs leading-relaxed">
-                    {Array.from(erroredDownloads.entries()).map(([modelName, dl]) => (
-                      <div key={modelName} className="mb-2 last:mb-0">
-                        <span className="text-[#f44747]">[error]</span>{' '}
-                        <span className="text-[#569cd6]">{modelName}</span>
-                        {dl.error ? (
-                          <>
-                            {': '}
-                            <span className="text-[#ce9178] whitespace-pre-wrap break-all">{dl.error}</span>
-                          </>
+                      type="button"
+                      onClick={() => openModelDetail(model)}
+                      className="w-full flex items-center gap-3 px-3 py-2.5 text-left hover:bg-muted/50 transition-colors group"
+                    >
+                      {/* Status indicator */}
+                      <div className="shrink-0">
+                        {hasError ? (
+                          <CircleX className="h-4 w-4 text-destructive" />
+                        ) : isDownloading ? (
+                          <Loader2 className="h-4 w-4 animate-spin text-muted-foreground" />
+                        ) : model.loaded ? (
+                          <CircleCheck className="h-4 w-4 text-accent" />
+                        ) : model.downloaded ? (
+                          <CircleCheck className="h-4 w-4 text-emerald-500" />
                        ) : (
-                          <>
-                            {': '}
-                            <span className="text-[#808080]">No error details available. Try downloading again.</span>
-                          </>
+                          <Download className="h-4 w-4 text-muted-foreground/50" />
                        )}
-                        <div className="text-[#6a9955] mt-0.5">
-                          started at {new Date(dl.started_at).toLocaleString()}
-                        </div>
                      </div>
-                    ))}
+
+                      {/* Name + inline progress */}
+                      <div className="flex-1 min-w-0">
+                        <span className="text-sm font-medium">{model.display_name}</span>
+                        {isDownloading &&
+                          (() => {
+                            const dl = downloadProgressMap.get(model.model_name);
+                            const pct = dl?.progress ?? 0;
+                            const hasProgress = dl && dl.total && dl.total > 0;
+                            return (
+                              <div className="mt-1 space-y-0.5">
+                                <Progress value={hasProgress ? pct : undefined} className="h-1" />
+                                <div className="text-[10px] text-muted-foreground truncate">
+                                  {hasProgress
+                                    ? `${formatBytes(dl.current ?? 0)} / ${formatBytes(dl.total!)} (${pct.toFixed(0)}%)`
+                                    : dl?.filename || 'Connecting...'}
+                                </div>
+                              </div>
+                            );
+                          })()}
+                      </div>
+
+                      {/* Right side info */}
+                      <div className="shrink-0 flex items-center gap-2">
+                        {hasError && (
+                          <Badge variant="destructive" className="text-[10px] h-5">
+                            Error
+                          </Badge>
+                        )}
+                        {model.loaded && (
+                          <Badge className="text-[10px] h-5 bg-accent/15 text-accent border-accent/30 hover:bg-accent/15">
+                            Loaded
+                          </Badge>
+                        )}
+                        {model.downloaded && !isDownloading && !hasError && (
+                          <span className="text-xs text-muted-foreground">
+                            {formatSize(model.size_mb)}
+                          </span>
+                        )}
+                        {!model.downloaded && !isDownloading && !hasError && (
+                          <span className="text-xs text-muted-foreground/60">Not downloaded</span>
+                        )}
+                        <ChevronRight className="h-4 w-4 text-muted-foreground/40 group-hover:text-muted-foreground transition-colors" />
+                      </div>
+                    </button>
+                  );
+                })}
+              </div>
+            </div>
+          ))}
+
+          {/* Error console */}
+          {errorCount > 0 && (
+            <div className="border rounded-lg overflow-hidden">
+              <div className="flex items-center justify-between px-3 py-1.5 bg-muted/50 text-xs font-medium text-muted-foreground">
+                <button
+                  type="button"
+                  onClick={() => setConsoleOpen((v) => !v)}
+                  className="flex items-center gap-2 hover:text-foreground transition-colors"
+                >
+                  {consoleOpen ? (
+                    <ChevronUp className="h-3.5 w-3.5" />
+                  ) : (
+                    <ChevronDown className="h-3.5 w-3.5" />
+                  )}
+                  <span>Problems</span>
+                  <Badge variant="destructive" className="text-[10px] h-4 px-1.5 rounded-full">
+                    {errorCount}
+                  </Badge>
+                </button>
+                <Button
+                  size="sm"
+                  variant="ghost"
+                  className="h-6 px-2 text-xs text-muted-foreground hover:text-foreground"
+                  onClick={() => clearAllMutation.mutate()}
+                  disabled={clearAllMutation.isPending}
+                >
+                  <RotateCcw className="h-3 w-3 mr-1" />
+                  Clear All
+                </Button>
+              </div>
+              {consoleOpen && (
+                <div className="bg-[#1e1e1e] text-[#d4d4d4] p-3 max-h-48 overflow-auto font-mono text-xs leading-relaxed">
+                  {Array.from(erroredDownloads.entries()).map(([modelName, dl]) => (
+                    <div key={modelName} className="mb-2 last:mb-0">
+                      <span className="text-[#f44747]">[error]</span>{' '}
+                      <span className="text-[#569cd6]">{modelName}</span>
+                      {dl.error ? (
+                        <>
+                          {': '}
+                          <span className="text-[#ce9178] whitespace-pre-wrap break-all">
+                            {dl.error}
+                          </span>
+                        </>
+                      ) : (
+                        <>
+                          {': '}
+                          <span className="text-[#808080]">
+                            No error details available. Try downloading again.
+                          </span>
+                        </>
+                      )}
+                      <div className="text-[#6a9955] mt-0.5">
+                        started at {new Date(dl.started_at).toLocaleString()}
+                      </div>
+                    </div>
+                  ))}
+                </div>
+              )}
+            </div>
+          )}
+        </div>
+      ) : null}
+
+      {/* Model Detail Modal */}
+      <Dialog open={detailOpen} onOpenChange={setDetailOpen}>
+        <DialogContent className="sm:max-w-md">
+          {freshSelectedModel && (
+            <>
+              <DialogHeader>
+                <DialogTitle>{freshSelectedModel.display_name}</DialogTitle>
+                <DialogDescription className="flex items-center gap-1.5">
+                  {freshSelectedModel.hf_repo_id ? (
+                    <a
+                      href={`https://huggingface.co/${freshSelectedModel.hf_repo_id}`}
+                      target="_blank"
+                      rel="noopener noreferrer"
+                      className="inline-flex items-center gap-1 hover:underline"
+                    >
+                      {freshSelectedModel.hf_repo_id}
+                      <ExternalLink className="h-3 w-3" />
+                    </a>
+                  ) : (
+                    freshSelectedModel.model_name
+                  )}
+                </DialogDescription>
+              </DialogHeader>
+
+              <div className="space-y-4 pt-2">
+                {/* Status badges */}
+                <div className="flex items-center gap-2 flex-wrap">
+                  {freshSelectedModel.loaded && (
+                    <Badge className="text-xs bg-accent/15 text-accent border-accent/30 hover:bg-accent/15">
+                      <CircleCheck className="h-3 w-3 mr-1" />
+                      Loaded
+                    </Badge>
+                  )}
+                  {freshSelectedModel.downloaded && !freshSelectedModel.loaded && (
+                    <Badge variant="secondary" className="text-xs">
+                      <CircleCheck className="h-3 w-3 mr-1" />
+                      Downloaded
+                    </Badge>
+                  )}
+                  {selectedState?.hasError && (
+                    <Badge variant="destructive" className="text-xs">
+                      <CircleX className="h-3 w-3 mr-1" />
+                      Error
+                    </Badge>
+                  )}
+                  {!freshSelectedModel.downloaded &&
+                    !selectedState?.isDownloading &&
+                    !selectedState?.hasError && (
+                      <Badge variant="outline" className="text-xs text-muted-foreground">
+                        Not downloaded
+                      </Badge>
+                    )}
+                </div>
+
+                {/* HuggingFace model card info */}
+                {hfLoading && freshSelectedModel.hf_repo_id && (
+                  <div className="flex items-center gap-2 text-xs text-muted-foreground py-2">
+                    <Loader2 className="h-3 w-3 animate-spin" />
+                    Loading model info...
                  </div>
                )}
+
+                {hfModelInfo && (
+                  <div className="space-y-3">
+                    {/* Stats row */}
+                    <div className="flex items-center gap-4 text-xs text-muted-foreground">
+                      <span className="flex items-center gap-1" title="Downloads">
+                        <Download className="h-3.5 w-3.5" />
+                        {formatDownloads(hfModelInfo.downloads)}
+                      </span>
+                      <span className="flex items-center gap-1" title="Likes">
+                        <Heart className="h-3.5 w-3.5" />
+                        {formatDownloads(hfModelInfo.likes)}
+                      </span>
+                      {license && (
+                        <span className="flex items-center gap-1" title="License">
+                          <Scale className="h-3.5 w-3.5" />
+                          {formatLicense(license)}
+                        </span>
+                      )}
+                    </div>
+
+                    {/* Pipeline tag + author */}
+                    <div className="flex flex-wrap gap-1.5">
+                      {hfModelInfo.pipeline_tag && (
+                        <Badge variant="outline" className="text-[10px]">
+                          {formatPipelineTag(hfModelInfo.pipeline_tag)}
+                        </Badge>
+                      )}
+                      {hfModelInfo.library_name && (
+                        <Badge variant="outline" className="text-[10px]">
+                          {hfModelInfo.library_name}
+                        </Badge>
+                      )}
+                      {hfModelInfo.author && (
+                        <Badge variant="outline" className="text-[10px]">
+                          by {hfModelInfo.author}
+                        </Badge>
+                      )}
+                    </div>
+
+                    {/* Languages */}
+                    {hfModelInfo.cardData?.language && hfModelInfo.cardData.language.length > 0 && (
+                      <div>
+                        <span className="text-xs text-muted-foreground">
+                          {hfModelInfo.cardData.language.length > 10
+                            ? `${hfModelInfo.cardData.language.length} languages supported`
+                            : `Languages: ${hfModelInfo.cardData.language.join(', ')}`}
+                        </span>
+                      </div>
+                    )}
+                  </div>
+                )}
+
+                {/* Disk size */}
+                {freshSelectedModel.downloaded && freshSelectedModel.size_mb && (
+                  <div className="flex items-center gap-2 text-sm text-muted-foreground">
+                    <HardDrive className="h-4 w-4" />
+                    <span>{formatSize(freshSelectedModel.size_mb)} on disk</span>
+                  </div>
+                )}
+
+                {/* Error detail */}
+                {selectedError?.error && (
+                  <div className="rounded-md bg-destructive/10 border border-destructive/20 p-3 text-xs text-destructive">
+                    {selectedError.error}
+                  </div>
+                )}
+
+                {/* Actions */}
+                <div className="flex items-center gap-2 pt-2 border-t">
+                  {selectedState?.hasError ? (
+                    <>
+                      <Button
+                        size="sm"
+                        onClick={() => handleDownload(freshSelectedModel.model_name)}
+                        variant="outline"
+                        className="flex-1"
+                      >
+                        <Download className="h-4 w-4 mr-2" />
+                        Retry Download
+                      </Button>
+                      <Button
+                        size="sm"
+                        onClick={() => handleCancel(freshSelectedModel.model_name)}
+                        variant="ghost"
+                        disabled={
+                          cancelMutation.isPending &&
+                          cancelMutation.variables === freshSelectedModel.model_name
+                        }
+                      >
+                        <X className="h-4 w-4" />
+                      </Button>
+                    </>
+                  ) : selectedState?.isDownloading ? (
+                    <>
+                      <div className="flex-1 space-y-2">
+                        {(() => {
+                          const dl = freshSelectedModel
+                            ? downloadProgressMap.get(freshSelectedModel.model_name)
+                            : undefined;
+                          const pct = dl?.progress ?? 0;
+                          const hasProgress = dl && dl.total && dl.total > 0;
+                          return (
+                            <>
+                              <Progress value={hasProgress ? pct : undefined} className="h-2" />
+                              <div className="text-xs text-muted-foreground">
+                                {hasProgress
+                                  ? `${formatBytes(dl.current ?? 0)} / ${formatBytes(dl.total!)} (${pct.toFixed(1)}%)`
+                                  : dl?.filename || 'Connecting to HuggingFace...'}
+                              </div>
+                            </>
+                          );
+                        })()}
+                      </div>
+                      <Button
+                        size="sm"
+                        onClick={() => handleCancel(freshSelectedModel.model_name)}
+                        variant="ghost"
+                        disabled={
+                          cancelMutation.isPending &&
+                          cancelMutation.variables === freshSelectedModel.model_name
+                        }
+                      >
+                        <X className="h-4 w-4" />
+                      </Button>
+                    </>
+                  ) : freshSelectedModel.downloaded ? (
+                    <Button
+                      size="sm"
+                      onClick={() => {
+                        setModelToDelete({
+                          name: freshSelectedModel.model_name,
+                          displayName: freshSelectedModel.display_name,
+                          sizeMb: freshSelectedModel.size_mb,
+                        });
+                        setDeleteDialogOpen(true);
+                      }}
+                      variant="outline"
+                      disabled={freshSelectedModel.loaded}
+                      title={
+                        freshSelectedModel.loaded ? 'Unload model before deleting' : 'Delete model'
+                      }
+                      className="flex-1"
+                    >
+                      <Trash2 className="h-4 w-4 mr-2" />
+                      {freshSelectedModel.loaded ? 'Unload to Delete' : 'Delete Model'}
+                    </Button>
+                  ) : (
+                    <Button
+                      size="sm"
+                      onClick={() => handleDownload(freshSelectedModel.model_name)}
+                      className="flex-1"
+                    >
+                      <Download className="h-4 w-4 mr-2" />
+                      Download
+                    </Button>
+                  )}
+                </div>
              </div>
-            )}
-          </div>
-        ) : null}
-      </CardContent>
+            </>
+          )}
+        </DialogContent>
+      </Dialog>

      {/* Delete Confirmation Dialog */}
      <AlertDialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
@@ -413,116 +773,6 @@ export function ModelManagement() {
          </AlertDialogFooter>
        </AlertDialogContent>
      </AlertDialog>
-    </Card>
-  );
-}
-
-interface ModelItemProps {
-  model: {
-    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;
-  onCancel: () => void;
-  isDownloading: boolean;  // Local state - true if user just clicked download
-  isCancelling: boolean;
-  isDismissed: boolean;
-  erroredDownload?: ActiveDownloadTask;
-  formatSize: (sizeMb?: number) => string;
-}
-
-function ModelItem({ model, onDownload, onDelete, onCancel, isDownloading, isCancelling, isDismissed, erroredDownload, formatSize }: ModelItemProps) {
-  // Use server's downloading state OR local state (for immediate feedback before server updates)
-  // Suppress downloading if user just dismissed/cancelled this model
-  const showDownloading = (model.downloading || isDownloading) && !erroredDownload && !isDismissed;
-
-  return (
-    <div className="flex items-center justify-between p-3 border rounded-lg">
-      <div className="flex-1 min-w-0">
-        <div className="flex items-center gap-2">
-          <span className="font-medium text-sm">{model.display_name}</span>
-          {model.loaded && (
-            <Badge variant="default" className="text-xs">
-              Loaded
-            </Badge>
-          )}
-          {model.downloaded && !model.loaded && !showDownloading && !erroredDownload && (
-            <Badge variant="secondary" className="text-xs">
-              Downloaded
-            </Badge>
-          )}
-          {erroredDownload && (
-            <Badge variant="destructive" className="text-xs">
-              Error
-            </Badge>
-          )}
-        </div>
-        {model.downloaded && model.size_mb && !showDownloading && !erroredDownload && (
-          <div className="text-xs text-muted-foreground mt-1">
-            Size: {formatSize(model.size_mb)}
-          </div>
-        )}
-      </div>
-      <div className="flex items-center gap-2 shrink-0 ml-2">
-        {erroredDownload ? (
-          <div className="flex items-center gap-2">
-            <Button size="sm" onClick={onDownload} variant="outline">
-              <Download className="h-4 w-4 mr-2" />
-              Retry
-            </Button>
-            <Button
-              size="sm"
-              onClick={onCancel}
-              variant="ghost"
-              disabled={isCancelling}
-              title="Dismiss error"
-            >
-              <X className="h-4 w-4" />
-            </Button>
-          </div>
-        ) : 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>
-            </div>
-            <Button
-              size="sm"
-              onClick={onDelete}
-              variant="outline"
-              disabled={model.loaded}
-              title={model.loaded ? 'Unload model before deleting' : 'Delete model'}
-            >
-              <Trash2 className="h-4 w-4" />
-            </Button>
-          </div>
-        ) : showDownloading ? (
-          <div className="flex items-center gap-2">
-            <Button size="sm" variant="outline" disabled>
-              <Loader2 className="h-4 w-4 mr-2 animate-spin" />
-              Downloading...
-            </Button>
-            <Button
-              size="sm"
-              onClick={onCancel}
-              variant="ghost"
-              disabled={isCancelling}
-              title="Cancel download"
-            >
-              <X className="h-4 w-4" />
-            </Button>
-          </div>
-        ) : (
-          <Button size="sm" onClick={onDownload} variant="outline">
-            <Download className="h-4 w-4 mr-2" />
-            Download
-          </Button>
-        )}
-      </div>
    </div>
  );
 }
@@ -1,5 +1,5 @@
-import { Link, useMatchRoute } from '@tanstack/react-router';
-import { Box, BookOpen, Loader2, Mic, Server, Speaker, Volume2 } from 'lucide-react';
+import { Link, useMatchRoute, useRouterState } from '@tanstack/react-router';
+import { BookOpen, BookText, Box, 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';
@@ -12,6 +12,7 @@ interface SidebarProps {
 const tabs = [
  { id: 'main', path: '/', icon: Volume2, label: 'Generate' },
  { id: 'stories', path: '/stories', icon: BookOpen, label: 'Stories' },
+  { id: 'audiobook', path: '/audiobook', icon: BookText, label: 'Audiobook' },
  { id: 'voices', path: '/voices', icon: Mic, label: 'Voices' },
  { id: 'audio', path: '/audio', icon: Speaker, label: 'Audio' },
  { id: 'models', path: '/models', icon: Box, label: 'Models' },
@@ -23,6 +24,9 @@ export function Sidebar({ isMacOS }: SidebarProps) {
  const audioUrl = usePlayerStore((state) => state.audioUrl);
  const isPlayerVisible = !!audioUrl;
  const matchRoute = useMatchRoute();
+  const pathname = useRouterState({
+    select: (state) => state.location.pathname,
+  });

  return (
    <div
@@ -41,10 +45,7 @@ export function Sidebar({ isMacOS }: SidebarProps) {
        {tabs.map((tab) => {
          const Icon = tab.icon;
          // For index route, use exact match; for others, use default matching
-          const isActive =
-            tab.path === '/'
-              ? matchRoute({ to: '/', exact: true })
-              : matchRoute({ to: tab.path });
+          const isActive = tab.path === '/' ? pathname === '/' : matchRoute({ to: tab.path });

          return (
            <Link
@@ -1,8 +1,11 @@
 import { FloatingGenerateBox } from '@/components/Generation/FloatingGenerateBox';
+import { usePlayerStore } from '@/stores/playerStore';
 import { StoryContent } from './StoryContent';
 import { StoryList } from './StoryList';

 export function StoriesTab() {
+  const audioUrl = usePlayerStore((state) => state.audioUrl);
+
  return (
    <div className="flex flex-col h-full min-h-0 overflow-hidden">
      {/* Main content area */}
@@ -18,7 +21,7 @@ export function StoriesTab() {
        </div>

        {/* Floating Generate Box - position is managed via storyStore.trackEditorHeight */}
-        <FloatingGenerateBox showVoiceSelector />
+        <FloatingGenerateBox showVoiceSelector isPlayerOpen={!!audioUrl} />
      </div>
    </div>
  );
@@ -125,6 +125,32 @@
    text-orientation: mixed;
    letter-spacing: 0.1em;
  }
+
+  .scrollbar-visible {
+    scrollbar-width: thin;
+    -ms-overflow-style: auto;
+    scrollbar-color: #d8ab4f #2b2b2b;
+  }
+
+  .scrollbar-visible::-webkit-scrollbar {
+    display: block;
+    width: 10px;
+    height: 10px;
+  }
+
+  .scrollbar-visible::-webkit-scrollbar-track {
+    background: #2b2b2b;
+  }
+
+  .scrollbar-visible::-webkit-scrollbar-thumb {
+    background: #d8ab4f;
+    border-radius: 9999px;
+    border: 2px solid #131313;
+  }
+
+  .scrollbar-visible::-webkit-scrollbar-thumb:hover {
+    background: #e2b85e;
+  }
 }

@keyframes fadeInScale {
@@ -34,6 +34,8 @@ export interface GenerationRequest {
  language: LanguageCode;
  seed?: number;
  model_size?: '1.7B' | '0.6B';
+  engine?: 'qwen' | 'luxtts' | 'chatterbox';
+  instruct?: string;
 }

 export interface GenerationResponse {
@@ -117,12 +119,29 @@ export interface ModelProgress {
 export interface ModelStatus {
  model_name: string;
  display_name: string;
+  hf_repo_id?: string; // HuggingFace repository ID
  downloaded: boolean;
  downloading: boolean; // True if download is in progress
  size_mb?: number;
  loaded: boolean;
 }

+export interface HuggingFaceModelInfo {
+  id: string;
+  author: string;
+  lastModified: string;
+  pipeline_tag?: string;
+  library_name?: string;
+  downloads: number;
+  likes: number;
+  tags: string[];
+  cardData?: {
+    license?: string;
+    language?: string[];
+    pipeline_tag?: string;
+  };
+}
+
 export interface ModelStatusListResponse {
  models: ModelStatus[];
 }
@@ -136,6 +155,10 @@ export interface ActiveDownloadTask {
  status: string;
  started_at: string;
  error?: string;
+  progress?: number; // 0-100 percentage
+  current?: number; // bytes downloaded
+  total?: number; // total bytes
+  filename?: string; // current file being downloaded
 }

 export interface ActiveGenerationTask {
@@ -1,6 +1,6 @@
 /**
- * Supported languages for Qwen3-TTS
- * Based on: https://github.com/QwenLM/Qwen3-TTS
+ * Supported languages for voice generation.
+ * Most languages use Qwen3-TTS; Hebrew uses Chatterbox TTS.
 */

 export const SUPPORTED_LANGUAGES = {
@@ -14,6 +14,7 @@ export const SUPPORTED_LANGUAGES = {
  pt: 'Portuguese',
  es: 'Spanish',
  it: 'Italian',
+  he: 'Hebrew',
 } as const;

 export type LanguageCode = keyof typeof SUPPORTED_LANGUAGES;
@@ -16,6 +16,7 @@ const generationSchema = z.object({
  seed: z.number().int().optional(),
  modelSize: z.enum(['1.7B', '0.6B']).optional(),
  instruct: z.string().max(500).optional(),
+  engine: z.enum(['qwen', 'luxtts', 'chatterbox']).optional(),
 });

 export type GenerationFormValues = z.infer<typeof generationSchema>;
@@ -47,6 +48,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
      seed: undefined,
      modelSize: '1.7B',
      instruct: '',
+      engine: 'qwen',
      ...options.defaultValues,
    },
  });
@@ -67,8 +69,21 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
    try {
      setIsGenerating(true);

-      const modelName = `qwen-tts-${data.modelSize}`;
-      const displayName = data.modelSize === '1.7B' ? 'Qwen TTS 1.7B' : 'Qwen TTS 0.6B';
+      const engine = data.engine || 'qwen';
+      const modelName =
+        engine === 'luxtts'
+          ? 'luxtts'
+          : engine === 'chatterbox'
+            ? 'chatterbox-tts'
+            : `qwen-tts-${data.modelSize}`;
+      const displayName =
+        engine === 'luxtts'
+          ? 'LuxTTS'
+          : engine === 'chatterbox'
+            ? 'Chatterbox TTS'
+            : data.modelSize === '1.7B'
+              ? 'Qwen TTS 1.7B'
+              : 'Qwen TTS 0.6B';

      try {
        const modelStatus = await apiClient.getModelStatus();
@@ -82,13 +97,15 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
        console.error('Failed to check model status:', error);
      }

+      const isQwen = engine === 'qwen';
      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,
+        model_size: isQwen ? data.modelSize : undefined,
+        engine,
+        instruct: isQwen ? data.instruct || undefined : undefined,
      });

      toast({
@@ -99,7 +116,14 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
      const audioUrl = apiClient.getAudioUrl(result.id);
      setAudioWithAutoPlay(audioUrl, result.id, selectedProfileId, data.text.substring(0, 50));

-      form.reset();
+      form.reset({
+        text: '',
+        language: data.language,
+        seed: undefined,
+        modelSize: data.modelSize,
+        instruct: '',
+        engine: data.engine,
+      });
      options.onSuccess?.(result.id);
    } catch (error) {
      toast({
@@ -0,0 +1,99 @@
+export interface TextChunk {
+  id: string;
+  text: string;
+  charCount: number;
+  wordCount: number;
+}
+
+function normalizeText(text: string): string {
+  return text.replace(/\r\n/g, '\n').replace(/\r/g, '\n').trim();
+}
+
+function splitParagraphIntoSentences(paragraph: string): string[] {
+  const trimmed = paragraph.trim();
+  if (!trimmed) {
+    return [];
+  }
+
+  const matches = trimmed.match(/[^.!?]+[.!?]+(?:["')\]]+)?|[^.!?]+$/g);
+  if (!matches || matches.length === 0) {
+    return [trimmed];
+  }
+
+  return matches.map((sentence) => sentence.trim()).filter(Boolean);
+}
+
+export function chunkText(
+  rawText: string,
+  targetChunkSize: number,
+  maxChunkSize: number,
+): TextChunk[] {
+  const text = normalizeText(rawText);
+  if (!text) {
+    return [];
+  }
+
+  const safeTarget = Math.max(200, Math.min(targetChunkSize, maxChunkSize));
+  const paragraphs = text
+    .split(/\n{2,}/)
+    .map((paragraph) => paragraph.trim())
+    .filter(Boolean);
+
+  const chunks: string[] = [];
+  let current = '';
+
+  const pushCurrent = () => {
+    const normalized = current.trim();
+    if (!normalized) {
+      return;
+    }
+    chunks.push(normalized);
+    current = '';
+  };
+
+  for (const paragraph of paragraphs) {
+    const sentences = splitParagraphIntoSentences(paragraph);
+
+    for (const sentence of sentences) {
+      // Keep sentence integrity. If one sentence exceeds maxChunkSize,
+      // keep it as a single oversized chunk and let UI ask for manual edit.
+      if (sentence.length > maxChunkSize) {
+        pushCurrent();
+        chunks.push(sentence);
+        continue;
+      }
+
+      if (!current) {
+        current = sentence;
+        continue;
+      }
+
+      const candidate = `${current} ${sentence}`;
+      if (candidate.length <= safeTarget) {
+        current = candidate;
+        continue;
+      }
+
+      if (candidate.length <= maxChunkSize && current.length < Math.floor(safeTarget * 0.75)) {
+        current = candidate;
+        continue;
+      }
+
+      pushCurrent();
+      current = sentence;
+    }
+
+    if (current.length >= Math.floor(safeTarget * 0.8)) {
+      pushCurrent();
+    }
+  }
+
+  pushCurrent();
+
+  return chunks.map((chunkTextValue, index) => ({
+    id: `chunk-${index + 1}`,
+    text: chunkTextValue,
+    charCount: chunkTextValue.length,
+    wordCount: chunkTextValue.split(/\s+/).filter(Boolean).length,
+  }));
+}
@@ -1,5 +1,6 @@
 import { createRootRoute, createRoute, createRouter, Outlet } from '@tanstack/react-router';
 import { AppFrame } from '@/components/AppFrame/AppFrame';
+import { AudiobookTab } from '@/components/AudiobookTab/AudiobookTab';
 import { AudioTab } from '@/components/AudioTab/AudioTab';
 import { MainEditor } from '@/components/MainEditor/MainEditor';
 import { ModelsTab } from '@/components/ModelsTab/ModelsTab';
@@ -10,6 +11,7 @@ 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');

@@ -86,6 +88,13 @@ const storiesRoute = createRoute({
  component: StoriesTab,
 });

+// Audiobook route
+const audiobookRoute = createRoute({
+  getParentRoute: () => rootRoute,
+  path: '/audiobook',
+  component: AudiobookTab,
+});
+
 // Voices route
 const voicesRoute = createRoute({
  getParentRoute: () => rootRoute,
@@ -118,6 +127,7 @@ const serverRoute = createRoute({
 const routeTree = rootRoute.addChildren([
  indexRoute,
  storiesRoute,
+  audiobookRoute,
  voicesRoute,
  audioRoute,
  modelsRoute,
@@ -334,18 +334,21 @@ python -m backend.main --host 0.0.0.0 --port 8000

 ## Usage Examples

+The desktop app, web client, and current development workflow use `http://localhost:17493` by default.
+If you launch the backend manually with a different host or port, substitute that address in the examples below.
+
 ### Creating a Voice Profile

 ```bash
 # 1. Create profile
-curl -X POST http://localhost:8000/profiles \
+curl -X POST http://localhost:17493/profiles \
  -H "Content-Type: application/json" \
  -d '{"name": "My Voice", "language": "en"}'

 # Response: {"id": "abc-123", ...}

 # 2. Add sample
-curl -X POST http://localhost:8000/profiles/abc-123/samples \
+curl -X POST http://localhost:17493/profiles/abc-123/samples \
  -F "[email protected]" \
  -F "reference_text=This is my voice sample"
 ```
@@ -353,7 +356,7 @@ curl -X POST http://localhost:8000/profiles/abc-123/samples \
 ### Generating Speech

 ```bash
-curl -X POST http://localhost:8000/generate \
+curl -X POST http://localhost:17493/generate \
  -H "Content-Type: application/json" \
  -d '{
    "profile_id": "abc-123",
@@ -365,13 +368,13 @@ curl -X POST http://localhost:8000/generate \
 # Response: {"id": "gen-456", "audio_path": "/path/to/audio.wav", ...}

 # Download audio
-curl http://localhost:8000/audio/gen-456 -o output.wav
+curl http://localhost:17493/audio/gen-456 -o output.wav
 ```

 ### Transcribing Audio

 ```bash
-curl -X POST http://localhost:8000/transcribe \
+curl -X POST http://localhost:17493/transcribe \
  -F "[email protected]" \
  -F "language=en"

@@ -386,12 +389,12 @@ Add multiple samples to a profile for better quality:

 ```bash
 # Add first sample
-curl -X POST http://localhost:8000/profiles/abc-123/samples \
+curl -X POST http://localhost:17493/profiles/abc-123/samples \
  -F "[email protected]" \
  -F "reference_text=First sample"

 # Add second sample
-curl -X POST http://localhost:8000/profiles/abc-123/samples \
+curl -X POST http://localhost:17493/profiles/abc-123/samples \
  -F "[email protected]" \
  -F "reference_text=Second sample"

@@ -412,10 +415,10 @@ Models are lazy-loaded and can be manually unloaded:

 ```bash
 # Unload TTS model
-curl -X POST http://localhost:8000/models/unload
+curl -X POST http://localhost:17493/models/unload

 # Load specific model size
-curl -X POST "http://localhost:8000/models/load?model_size=0.6B"
+curl -X POST "http://localhost:17493/models/load?model_size=0.6B"
 ```

 ## Error Handling
@@ -4,6 +4,7 @@ Backend abstraction layer for TTS and STT.
 Provides a unified interface for MLX and PyTorch backends.
 """

+import threading
 from typing import Protocol, Optional, Tuple, List
 from typing_extensions import runtime_checkable
 import numpy as np
@@ -112,29 +113,69 @@ class STTBackend(Protocol):

 # Global backend instances
 _tts_backend: Optional[TTSBackend] = None
+_tts_backends: dict[str, TTSBackend] = {}
+_tts_backends_lock = threading.Lock()
 _stt_backend: Optional[STTBackend] = None

+# Supported TTS engines
+TTS_ENGINES = {
+    "qwen": "Qwen TTS",
+    "luxtts": "LuxTTS",
+    "chatterbox": "Chatterbox TTS",
+}
+

 def get_tts_backend() -> TTSBackend:
    """
-    Get or create TTS backend instance based on platform.
+    Get or create the default (Qwen) TTS backend instance based on platform.
    
    Returns:
        TTS backend instance (MLX or PyTorch)
    """
-    global _tts_backend
+    return get_tts_backend_for_engine("qwen")
+
+
+def get_tts_backend_for_engine(engine: str) -> TTSBackend:
+    """
+    Get or create a TTS backend for the given engine.
    
-    if _tts_backend is None:
-        backend_type = get_backend_type()
+    Args:
+        engine: Engine name ("qwen" or "luxtts")
+    
+    Returns:
+        TTS backend instance
+    """
+    global _tts_backends
+    
+    # Fast path: check without lock
+    if engine in _tts_backends:
+        return _tts_backends[engine]
+    
+    # Slow path: create with lock to avoid duplicate instantiation
+    with _tts_backends_lock:
+        # Double-check after acquiring lock
+        if engine in _tts_backends:
+            return _tts_backends[engine]
        
-        if backend_type == "mlx":
-            from .mlx_backend import MLXTTSBackend
-            _tts_backend = MLXTTSBackend()
+        if engine == "qwen":
+            backend_type = get_backend_type()
+            if backend_type == "mlx":
+                from .mlx_backend import MLXTTSBackend
+                backend = MLXTTSBackend()
+            else:
+                from .pytorch_backend import PyTorchTTSBackend
+                backend = PyTorchTTSBackend()
+        elif engine == "luxtts":
+            from .luxtts_backend import LuxTTSBackend
+            backend = LuxTTSBackend()
+        elif engine == "chatterbox":
+            from .chatterbox_backend import ChatterboxTTSBackend
+            backend = ChatterboxTTSBackend()
        else:
-            from .pytorch_backend import PyTorchTTSBackend
-            _tts_backend = PyTorchTTSBackend()
-    
-    return _tts_backend
+            raise ValueError(f"Unknown TTS engine: {engine}. Supported: {list(TTS_ENGINES.keys())}")
+        
+        _tts_backends[engine] = backend
+        return backend


 def get_stt_backend() -> STTBackend:
@@ -161,6 +202,7 @@ def get_stt_backend() -> STTBackend:

 def reset_backends():
    """Reset backend instances (useful for testing)."""
-    global _tts_backend, _stt_backend
+    global _tts_backend, _tts_backends, _stt_backend
    _tts_backend = None
+    _tts_backends.clear()
    _stt_backend = None
@@ -0,0 +1,326 @@
+"""
+Chatterbox TTS backend implementation.
+
+Wraps ChatterboxMultilingualTTS from chatterbox-tts for zero-shot
+voice cloning. Supports 23 languages including Hebrew. Forces CPU
+on macOS due to known MPS tensor issues.
+"""
+
+import asyncio
+import logging
+import platform
+import threading
+from pathlib import Path
+from typing import ClassVar, List, Optional, Tuple
+
+import numpy as np
+
+from . import TTSBackend
+from ..utils.audio import normalize_audio, load_audio
+from ..utils.progress import get_progress_manager
+from ..utils.tasks import get_task_manager
+
+logger = logging.getLogger(__name__)
+
+CHATTERBOX_HF_REPO = "ResembleAI/chatterbox"
+
+# Files that must be present for the multilingual model
+_MTL_WEIGHT_FILES = [
+    "t3_mtl23ls_v2.safetensors",
+    "s3gen.pt",
+    "ve.pt",
+]
+
+
+class ChatterboxTTSBackend:
+    """Chatterbox Multilingual TTS backend for voice cloning."""
+
+    # Class-level lock for torch.load monkey-patching
+    _load_lock: ClassVar[threading.Lock] = threading.Lock()
+
+    def __init__(self):
+        self.model = None
+        self.model_size = "default"
+        self._device = None
+        self._model_load_lock = asyncio.Lock()
+
+    def _get_device(self) -> str:
+        """Get the best available device. Forces CPU on macOS (MPS issue)."""
+        if platform.system() == "Darwin":
+            return "cpu"
+        try:
+            import torch
+
+            if torch.cuda.is_available():
+                return "cuda"
+        except ImportError:
+            pass
+        return "cpu"
+
+    def is_loaded(self) -> bool:
+        return self.model is not None
+
+    def _get_model_path(self, model_size: str = "default") -> str:
+        return CHATTERBOX_HF_REPO
+
+    def _is_model_cached(self, model_size: str = "default") -> bool:
+        """Check if the Chatterbox multilingual model is cached locally."""
+        try:
+            from huggingface_hub import constants as hf_constants
+
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / (
+                "models--" + CHATTERBOX_HF_REPO.replace("/", "--")
+            )
+
+            if not repo_cache.exists():
+                return False
+
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                return False
+
+            # Check for multilingual weight files
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                for fname in _MTL_WEIGHT_FILES:
+                    if not any(snapshots_dir.rglob(fname)):
+                        return False
+                return True
+
+            return False
+        except Exception as e:
+            logger.warning(f"Error checking Chatterbox cache: {e}")
+            return False
+
+    async def load_model(self, model_size: str = "default") -> None:
+        """Load the Chatterbox multilingual model."""
+        if self.model is not None:
+            return
+        async with self._model_load_lock:
+            if self.model is not None:
+                return
+            await asyncio.to_thread(self._load_model_sync)
+
+    def _load_model_sync(self):
+        """Synchronous model loading."""
+        from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+
+        progress_manager = get_progress_manager()
+        task_manager = get_task_manager()
+        model_name = "chatterbox-tts"
+
+        is_cached = self._is_model_cached()
+
+        # Set up HF progress tracking (intercepts tqdm for file-level progress)
+        progress_callback = create_hf_progress_callback(model_name, progress_manager)
+        tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+        tracker_context = tracker.patch_download()
+        tracker_context.__enter__()
+
+        if not is_cached:
+            task_manager.start_download(model_name)
+            progress_manager.update_progress(
+                model_name=model_name,
+                current=0,
+                total=0,
+                filename="Connecting to HuggingFace...",
+                status="downloading",
+            )
+
+        try:
+            device = self._get_device()
+            self._device = device
+
+            logger.info(f"Loading Chatterbox Multilingual TTS on {device}...")
+
+            import torch
+            from chatterbox.mtl_tts import ChatterboxMultilingualTTS
+
+            # Monkey-patch torch.load for CPU loading. The model's .pt files
+            # were saved on CUDA; from_pretrained() doesn't pass map_location
+            # so loading on CPU fails without this.
+            try:
+                if device == "cpu":
+                    _orig_torch_load = torch.load
+
+                    def _patched_load(*args, **kwargs):
+                        kwargs.setdefault("map_location", "cpu")
+                        return _orig_torch_load(*args, **kwargs)
+
+                    with ChatterboxTTSBackend._load_lock:
+                        torch.load = _patched_load
+                        try:
+                            self.model = ChatterboxMultilingualTTS.from_pretrained(
+                                device=device,
+                            )
+                        finally:
+                            torch.load = _orig_torch_load
+                else:
+                    self.model = ChatterboxMultilingualTTS.from_pretrained(
+                        device=device,
+                    )
+            finally:
+                tracker_context.__exit__(None, None, None)
+
+            # Fix: transformers >= 4.36 defaults LlamaModel to sdpa attention
+            # which doesn't support output_attentions=True (needed by
+            # Chatterbox's AlignmentStreamAnalyzer). Force eager attention.
+            t3_tfmr = self.model.t3.tfmr
+            if hasattr(t3_tfmr, "config") and hasattr(
+                t3_tfmr.config, "_attn_implementation"
+            ):
+                t3_tfmr.config._attn_implementation = "eager"
+                for layer in getattr(t3_tfmr, "layers", []):
+                    if hasattr(layer, "self_attn"):
+                        layer.self_attn._attn_implementation = "eager"
+
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+
+            logger.info("Chatterbox Multilingual TTS loaded successfully")
+
+        except ImportError as e:
+            logger.error(
+                "chatterbox-tts package not found. "
+                "Install with: pip install chatterbox-tts"
+            )
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+        except Exception as e:
+            logger.error(f"Failed to load Chatterbox: {e}")
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        if self.model is not None:
+            device = self._device
+            del self.model
+            self.model = None
+            self._device = None
+            if device == "cuda":
+                import torch
+
+                torch.cuda.empty_cache()
+            logger.info("Chatterbox unloaded")
+
+    async def create_voice_prompt(
+        self,
+        audio_path: str,
+        reference_text: str,
+        use_cache: bool = True,
+    ) -> Tuple[dict, bool]:
+        """
+        Create voice prompt from reference audio.
+
+        Chatterbox processes reference audio at generation time, so the
+        prompt just stores the file path. The actual audio is loaded by
+        model.generate() via audio_prompt_path.
+        """
+        voice_prompt = {
+            "ref_audio": str(audio_path),
+            "ref_text": reference_text,
+        }
+        return voice_prompt, False
+
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """Combine multiple reference samples."""
+        combined_audio = []
+        for path in audio_paths:
+            audio, _sr = load_audio(path)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        combined_text = " ".join(reference_texts)
+        return mixed, combined_text
+
+    # Per-language generation defaults. Lower temp + higher cfg = clearer speech.
+    _LANG_DEFAULTS: ClassVar[dict] = {
+        "he": {
+            "exaggeration": 0.4,
+            "cfg_weight": 0.7,
+            "temperature": 0.65,
+            "repetition_penalty": 2.5,
+        },
+    }
+    _GLOBAL_DEFAULTS: ClassVar[dict] = {
+        "exaggeration": 0.5,
+        "cfg_weight": 0.5,
+        "temperature": 0.8,
+        "repetition_penalty": 2.0,
+    }
+
+    async def generate(
+        self,
+        text: str,
+        voice_prompt: dict,
+        language: str = "en",
+        seed: Optional[int] = None,
+        instruct: Optional[str] = None,
+    ) -> Tuple[np.ndarray, int]:
+        """
+        Generate audio using Chatterbox Multilingual TTS.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Dict with ref_audio path
+            language: BCP-47 language code
+            seed: Random seed for reproducibility
+            instruct: Unused (protocol compatibility)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model()
+
+        ref_audio = voice_prompt.get("ref_audio")
+        if ref_audio and not Path(ref_audio).exists():
+            logger.warning(f"Reference audio not found: {ref_audio}")
+            ref_audio = None
+
+        # Merge language-specific defaults with global defaults
+        lang_defaults = self._LANG_DEFAULTS.get(language, self._GLOBAL_DEFAULTS)
+
+        def _generate_sync():
+            import torch
+
+            if seed is not None:
+                torch.manual_seed(seed)
+
+            logger.info(f"[Chatterbox] Generating: lang={language}")
+
+            wav = self.model.generate(
+                text,
+                language_id=language,
+                audio_prompt_path=ref_audio,
+                exaggeration=lang_defaults["exaggeration"],
+                cfg_weight=lang_defaults["cfg_weight"],
+                temperature=lang_defaults["temperature"],
+                repetition_penalty=lang_defaults["repetition_penalty"],
+            )
+
+            # Convert tensor -> numpy
+            if isinstance(wav, torch.Tensor):
+                audio = wav.squeeze().cpu().numpy().astype(np.float32)
+            else:
+                audio = np.asarray(wav, dtype=np.float32)
+
+            sample_rate = (
+                getattr(self.model, "sr", None)
+                or getattr(self.model, "sample_rate", 24000)
+            )
+
+            return audio, sample_rate
+
+        return await asyncio.to_thread(_generate_sync)
@@ -0,0 +1,275 @@
+"""
+LuxTTS backend implementation.
+
+Wraps the LuxTTS (ZipVoice) model for zero-shot voice cloning.
+~1GB VRAM, 48kHz output, 150x realtime on CPU.
+"""
+
+import asyncio
+import logging
+from pathlib import Path
+from typing import List, Optional, Tuple
+
+import numpy as np
+
+from . import TTSBackend
+from ..utils.audio import normalize_audio, load_audio
+from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
+from ..utils.progress import get_progress_manager
+from ..utils.tasks import get_task_manager
+
+logger = logging.getLogger(__name__)
+
+# HuggingFace repo for model weight detection
+LUXTTS_HF_REPO = "YatharthS/LuxTTS"
+
+
+class LuxTTSBackend:
+    """LuxTTS backend for zero-shot voice cloning."""
+
+    def __init__(self):
+        self.model = None
+        self.model_size = "default"  # LuxTTS has only one model size
+        self._device = None
+
+    def _get_device(self) -> str:
+        """Get the best available device."""
+        import torch
+
+        if torch.cuda.is_available():
+            return "cuda"
+        if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+            return "mps"
+        return "cpu"
+
+    def is_loaded(self) -> bool:
+        return self.model is not None
+
+    @property
+    def device(self) -> str:
+        if self._device is None:
+            self._device = self._get_device()
+        return self._device
+
+    def _get_model_path(self, model_size: str) -> str:
+        return LUXTTS_HF_REPO
+
+    def _is_model_cached(self, model_size: str = "default") -> bool:
+        """Check if LuxTTS model weights are cached locally."""
+        try:
+            from huggingface_hub import constants as hf_constants
+
+            repo_cache = (
+                Path(hf_constants.HF_HUB_CACHE)
+                / ("models--" + LUXTTS_HF_REPO.replace("/", "--"))
+            )
+
+            if not repo_cache.exists():
+                return False
+
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                return False
+
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = any(snapshots_dir.rglob("*.pt")) or any(
+                    snapshots_dir.rglob("*.safetensors")
+                ) or any(snapshots_dir.rglob("*.onnx")) or any(
+                    snapshots_dir.rglob("*.bin")
+                )
+                return has_weights
+
+            return False
+        except Exception as e:
+            logger.warning(f"Error checking LuxTTS cache: {e}")
+            return False
+
+    async def load_model(self, model_size: str = "default") -> None:
+        """Load the LuxTTS model."""
+        if self.model is not None:
+            return
+
+        await asyncio.to_thread(self._load_model_sync)
+
+    def _load_model_sync(self):
+        """Synchronous model loading."""
+        from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+
+        progress_manager = get_progress_manager()
+        task_manager = get_task_manager()
+        model_name = "luxtts"
+
+        is_cached = self._is_model_cached()
+
+        # Set up HF progress tracking (intercepts tqdm for file-level progress)
+        progress_callback = create_hf_progress_callback(model_name, progress_manager)
+        tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+        tracker_context = tracker.patch_download()
+        tracker_context.__enter__()
+
+        if not is_cached:
+            task_manager.start_download(model_name)
+            progress_manager.update_progress(
+                model_name=model_name,
+                current=0,
+                total=0,
+                filename="Connecting to HuggingFace...",
+                status="downloading",
+            )
+
+        try:
+            from zipvoice.luxvoice import LuxTTS
+
+            device = self.device
+            logger.info(f"Loading LuxTTS on {device}...")
+
+            # LuxTTS constructor downloads model and loads everything
+            try:
+                if device == "cpu":
+                    import os
+                    threads = os.cpu_count() or 4
+                    self.model = LuxTTS(
+                        model_path=LUXTTS_HF_REPO,
+                        device="cpu",
+                        threads=min(threads, 8),
+                    )
+                else:
+                    self.model = LuxTTS(
+                        model_path=LUXTTS_HF_REPO,
+                        device=device,
+                    )
+            finally:
+                tracker_context.__exit__(None, None, None)
+
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+
+            logger.info("LuxTTS loaded successfully")
+
+        except Exception as e:
+            logger.error(f"Failed to load LuxTTS: {e}")
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        if self.model is not None:
+            del self.model
+            self.model = None
+
+            import torch
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+
+            logger.info("LuxTTS unloaded")
+
+    async def create_voice_prompt(
+        self,
+        audio_path: str,
+        reference_text: str,
+        use_cache: bool = True,
+    ) -> Tuple[dict, bool]:
+        """
+        Create voice prompt from reference audio.
+
+        LuxTTS uses its own encode_prompt() which runs Whisper ASR internally
+        to transcribe the reference. The reference_text parameter is not used
+        by LuxTTS itself, but we include it in the cache key for consistency.
+        """
+        await self.load_model()
+
+        # Compute cache key once for both lookup and storage
+        cache_key = ("luxtts_" + get_cache_key(audio_path, reference_text)) if use_cache else None
+
+        if cache_key:
+            cached = get_cached_voice_prompt(cache_key)
+            if cached is not None and isinstance(cached, dict):
+                return cached, True
+
+        def _encode_sync():
+            return self.model.encode_prompt(
+                prompt_audio=str(audio_path),
+                duration=5,
+                rms=0.01,
+            )
+
+        encoded = await asyncio.to_thread(_encode_sync)
+
+        if cache_key:
+            cache_voice_prompt(cache_key, encoded)
+
+        return encoded, False
+
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple reference samples.
+
+        LuxTTS doesn't have native multi-prompt support, so we concatenate
+        the audio and let encode_prompt handle the combined clip.
+        """
+        combined_audio = []
+        for path in audio_paths:
+            audio, _sr = load_audio(path, sample_rate=24000)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        combined_text = " ".join(reference_texts)
+
+        return mixed, combined_text
+
+    async def generate(
+        self,
+        text: str,
+        voice_prompt: dict,
+        language: str = "en",
+        seed: Optional[int] = None,
+        instruct: Optional[str] = None,
+    ) -> Tuple[np.ndarray, int]:
+        """
+        Generate audio from text using LuxTTS.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Encoded prompt dict from encode_prompt()
+            language: Language code (LuxTTS is English-focused)
+            seed: Random seed for reproducibility
+            instruct: Not supported by LuxTTS (ignored)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model()
+
+        def _generate_sync():
+            import torch
+
+            if seed is not None:
+                torch.manual_seed(seed)
+                if torch.cuda.is_available():
+                    torch.cuda.manual_seed(seed)
+
+            wav = self.model.generate_speech(
+                text=text,
+                encode_dict=voice_prompt,
+                num_steps=4,
+                guidance_scale=3.0,
+                t_shift=0.5,
+                speed=1.0,
+                return_smooth=False,  # 48kHz output
+            )
+
+            # LuxTTS returns a tensor (may be on GPU/MPS), move to CPU first
+            audio = wav.detach().cpu().numpy().squeeze()
+            return audio, 48000
+
+        return await asyncio.to_thread(_generate_sync)
@@ -48,6 +48,18 @@ from .utils.tasks import get_task_manager
 from .utils.cache import clear_voice_prompt_cache
 from .platform_detect import get_backend_type

+# Keep references to fire-and-forget background tasks to prevent GC
+_background_tasks: set = set()
+
+
+def _create_background_task(coro) -> asyncio.Task:
+    """Create a background task and prevent it from being garbage collected."""
+    task = asyncio.create_task(coro)
+    _background_tasks.add(task)
+    task.add_done_callback(_background_tasks.discard)
+    return task
+
+
 app = FastAPI(
    title="voicebox API",
    description="Production-quality Qwen3-TTS voice cloning API",
@@ -222,7 +234,10 @@ async def create_profile(
    """Create a new voice profile."""
    try:
        return await profiles.create_profile(data, db)
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
    except Exception as e:
+        # Fallback for unexpected errors
        raise HTTPException(status_code=400, detail=str(e))


@@ -278,10 +293,13 @@ async def update_profile(
    db: Session = Depends(get_db),
 ):
    """Update a voice profile."""
-    profile = await profiles.update_profile(profile_id, data, db)
-    if not profile:
-        raise HTTPException(status_code=404, detail="Profile not found")
-    return profile
+    try:
+        profile = await profiles.update_profile(profile_id, data, db)
+        if not profile:
+            raise HTTPException(status_code=404, detail="Profile not found")
+        return profile
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))


@app.delete("/profiles/{profile_id}")
@@ -602,47 +620,92 @@ async def generate_speech(
            raise HTTPException(status_code=404, detail="Profile not found")
        
        # Generate audio
+        from .backends import get_tts_backend_for_engine

-        # Resolve model size and load the correct model FIRST.
-        # This must happen before create_voice_prompt_for_profile because that
-        # function calls load_model_async(None), which falls back to self.model_size.
-        # If the model is already loaded with the right size at that point, it
-        # returns immediately and the voice prompt is created by the correct model.
-        tts_model = tts.get_tts_model()
+        engine = data.engine or "qwen"
+        tts_model = get_tts_backend_for_engine(engine)
+
+        # Resolve model size (only relevant for Qwen engine)
        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 not tts_model._is_model_cached(model_size):
-            # Model is not fully cached — kick off a background download and tell
-            # the client to retry once it's ready.
-            model_name = f"qwen-tts-{model_size}"
+        if engine == "qwen":
+            if not tts_model._is_model_cached(model_size):
+                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))
+                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())
+                task_manager.start_download(model_name)
+                _create_background_task(download_model_background())

-            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,
-                },
-            )
+                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,
+                    },
+                )

-        # Load (or switch to) the requested model before building the voice prompt
-        await tts_model.load_model_async(model_size)
+            # Load (or switch to) the requested model
+            await tts_model.load_model_async(model_size)
+        elif engine == "luxtts":
+            if not tts_model._is_model_cached():
+                model_name = "luxtts"

-        # Create voice prompt from profile (model is already loaded with correct size)
+                async def download_luxtts_background():
+                    try:
+                        await tts_model.load_model()
+                    except Exception as e:
+                        task_manager.error_download(model_name, str(e))
+
+                task_manager.start_download(model_name)
+                _create_background_task(download_luxtts_background())
+
+                raise HTTPException(
+                    status_code=202,
+                    detail={
+                        "message": "LuxTTS model is being downloaded. Please wait and try again.",
+                        "model_name": model_name,
+                        "downloading": True,
+                    },
+                )
+
+            await tts_model.load_model()
+        elif engine == "chatterbox":
+            if not tts_model._is_model_cached():
+                model_name = "chatterbox-tts"
+
+                async def download_chatterbox_background():
+                    try:
+                        await tts_model.load_model()
+                    except Exception as e:
+                        task_manager.error_download(model_name, str(e))
+
+                task_manager.start_download(model_name)
+                asyncio.create_task(download_chatterbox_background())
+
+                raise HTTPException(
+                    status_code=202,
+                    detail={
+                        "message": "Chatterbox model is being downloaded. Please wait and try again.",
+                        "model_name": model_name,
+                        "downloading": True,
+                    },
+                )
+
+            await tts_model.load_model()
+
+        # Create voice prompt from profile
        voice_prompt = await profiles.create_voice_prompt_for_profile(
            data.profile_id,
            db,
+            use_cache=True,
+            engine=engine,
        )

        audio, sample_rate = await tts_model.generate(
@@ -653,6 +716,11 @@ async def generate_speech(
            data.instruct,
        )

+        # Trim trailing silence/hallucination for Chatterbox output
+        if engine == "chatterbox":
+            from .utils.audio import trim_tts_output
+            audio = trim_tts_output(audio, sample_rate)
+
        # Calculate duration
        duration = len(audio) / sample_rate

@@ -699,23 +767,41 @@ async def stream_speech(
    playing audio before the entire file has been received.  This endpoint
    does NOT create a history entry — use /generate for that.
    """
+    from .backends import get_tts_backend_for_engine
+
    profile = await profiles.get_profile(data.profile_id, db)
    if not profile:
        raise HTTPException(status_code=404, detail="Profile not found")

-    tts_model = tts.get_tts_model()
+    engine = data.engine or "qwen"
+    tts_model = get_tts_backend_for_engine(engine)
    model_size = data.model_size or "1.7B"

-    if not tts_model._is_model_cached(model_size):
-        raise HTTPException(
-            status_code=400,
-            detail=f"Model {model_size} is not downloaded yet. Use /generate to trigger a download.",
-        )
+    if engine == "qwen":
+        if not tts_model._is_model_cached(model_size):
+            raise HTTPException(
+                status_code=400,
+                detail=f"Model {model_size} is not downloaded yet. Use /generate to trigger a download.",
+            )
+        await tts_model.load_model_async(model_size)
+    elif engine == "luxtts":
+        if not tts_model._is_model_cached():
+            raise HTTPException(
+                status_code=400,
+                detail="LuxTTS model is not downloaded yet. Use /generate to trigger a download.",
+            )
+        await tts_model.load_model()
+    elif engine == "chatterbox":
+        if not tts_model._is_model_cached():
+            raise HTTPException(
+                status_code=400,
+                detail="Chatterbox model is not downloaded yet. Use /generate to trigger a download.",
+            )
+        await tts_model.load_model()

-    # Load the correct model before building the voice prompt (fixes issue #96)
-    await tts_model.load_model_async(model_size)
-
-    voice_prompt = await profiles.create_voice_prompt_for_profile(data.profile_id, db)
+    voice_prompt = await profiles.create_voice_prompt_for_profile(
+        data.profile_id, db, engine=engine,
+    )

    audio, sample_rate = await tts_model.generate(
        data.text,
@@ -725,6 +811,11 @@ async def stream_speech(
        data.instruct,
    )

+    # Trim trailing silence/hallucination for Chatterbox output
+    if engine == "chatterbox":
+        from .utils.audio import trim_tts_output
+        audio = trim_tts_output(audio, sample_rate)
+
    wav_bytes = tts.audio_to_wav_bytes(audio, sample_rate)

    async def _wav_stream():
@@ -953,7 +1044,7 @@ async def transcribe_audio(
                    get_task_manager().error_download(progress_model_name, str(e))

            get_task_manager().start_download(progress_model_name)
-            asyncio.create_task(download_whisper_background())
+            _create_background_task(download_whisper_background())

            # Return 202 Accepted
            raise HTTPException(
@@ -1324,6 +1415,24 @@ async def get_model_status():
        whisper_medium_id = "openai/whisper-medium"
        whisper_large_id = "openai/whisper-large-v3"
    
+    # Check if LuxTTS backend is loaded
+    def check_luxtts_loaded():
+        try:
+            from .backends import get_tts_backend_for_engine
+            backend = get_tts_backend_for_engine("luxtts")
+            return backend.is_loaded()
+        except Exception:
+            return False
+
+    # Check if Chatterbox backend is loaded
+    def check_chatterbox_loaded():
+        try:
+            from .backends import get_tts_backend_for_engine
+            backend = get_tts_backend_for_engine("chatterbox")
+            return backend.is_loaded()
+        except Exception:
+            return False
+
    model_configs = [
        {
            "model_name": "qwen-tts-1.7B",
@@ -1339,6 +1448,20 @@ async def get_model_status():
            "model_size": "0.6B",
            "check_loaded": lambda: check_tts_loaded("0.6B"),
        },
+        {
+            "model_name": "luxtts",
+            "display_name": "LuxTTS (Fast, CPU-friendly)",
+            "hf_repo_id": "YatharthS/LuxTTS",
+            "model_size": "default",
+            "check_loaded": check_luxtts_loaded,
+        },
+        {
+            "model_name": "chatterbox-tts",
+            "display_name": "Chatterbox TTS (Multilingual)",
+            "hf_repo_id": "ResembleAI/chatterbox",
+            "model_size": "default",
+            "check_loaded": check_chatterbox_loaded,
+        },
        {
            "model_name": "whisper-base",
            "display_name": "Whisper Base",
@@ -1490,6 +1613,7 @@ async def get_model_status():
            statuses.append(models.ModelStatus(
                model_name=config["model_name"],
                display_name=config["display_name"],
+                hf_repo_id=config["hf_repo_id"],
                downloaded=downloaded,
                downloading=is_downloading,
                size_mb=size_mb,
@@ -1508,6 +1632,7 @@ async def get_model_status():
            statuses.append(models.ModelStatus(
                model_name=config["model_name"],
                display_name=config["display_name"],
+                hf_repo_id=config["hf_repo_id"],
                downloaded=False,  # Assume not downloaded if check failed
                downloading=is_downloading,
                size_mb=None,
@@ -1521,6 +1646,7 @@ async def get_model_status():
 async def trigger_model_download(request: models.ModelDownloadRequest):
    """Trigger download of a specific model."""
    import asyncio
+    from .backends import get_tts_backend_for_engine
    
    task_manager = get_task_manager()
    progress_manager = get_progress_manager()
@@ -1534,6 +1660,14 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
            "model_size": "0.6B",
            "load_func": lambda: tts.get_tts_model().load_model("0.6B"),
        },
+        "luxtts": {
+            "model_size": "default",
+            "load_func": lambda: get_tts_backend_for_engine("luxtts").load_model(),
+        },
+        "chatterbox-tts": {
+            "model_size": "default",
+            "load_func": lambda: get_tts_backend_for_engine("chatterbox").load_model(),
+        },
        "whisper-base": {
            "model_size": "base",
            "load_func": lambda: transcribe.get_whisper_model().load_model("base"),
@@ -1585,7 +1719,7 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
    )

    # Start download in background task (don't await)
-    asyncio.create_task(download_in_background())
+    _create_background_task(download_in_background())

    # Return immediately - frontend should poll progress endpoint
    return {"message": f"Model {request.model_name} download started"}
@@ -1646,6 +1780,16 @@ async def delete_model(model_name: str):
            "model_size": "0.6B",
            "model_type": "tts",
        },
+        "luxtts": {
+            "hf_repo_id": "YatharthS/LuxTTS",
+            "model_size": "default",
+            "model_type": "luxtts",
+        },
+        "chatterbox-tts": {
+            "hf_repo_id": "ResembleAI/chatterbox",
+            "model_size": "default",
+            "model_type": "chatterbox",
+        },
        "whisper-base": {
            "hf_repo_id": "openai/whisper-base",
            "model_size": "base",
@@ -1680,6 +1824,16 @@ async def delete_model(model_name: str):
            tts_model = tts.get_tts_model()
            if tts_model.is_loaded() and tts_model.model_size == config["model_size"]:
                tts.unload_tts_model()
+        elif config["model_type"] == "luxtts":
+            from .backends import get_tts_backend_for_engine
+            luxtts = get_tts_backend_for_engine("luxtts")
+            if luxtts.is_loaded():
+                luxtts.unload_model()
+        elif config["model_type"] == "chatterbox":
+            from .backends import get_tts_backend_for_engine
+            chatterbox = get_tts_backend_for_engine("chatterbox")
+            if chatterbox.is_loaded():
+                chatterbox.unload_model()
        elif config["model_type"] == "whisper":
            whisper_model = transcribe.get_whisper_model()
            if whisper_model.is_loaded() and whisper_model.model_size == config["model_size"]:
@@ -1758,11 +1912,22 @@ async def get_active_tasks():
                    pm_data = progress_manager._progress.get(model_name)
                    if pm_data:
                        error = pm_data.get("error")
+            # Include progress data if available
+            prog = progress or {}
+            if not prog:
+                with progress_manager._lock:
+                    pm_data = progress_manager._progress.get(model_name)
+                    if pm_data:
+                        prog = pm_data
            active_downloads.append(models.ActiveDownloadTask(
                model_name=model_name,
                status=task.status,
                started_at=task.started_at,
                error=error,
+                progress=prog.get("progress"),
+                current=prog.get("current"),
+                total=prog.get("total"),
+                filename=prog.get("filename"),
            ))
        elif progress:
            # Progress exists but no task - create from progress data
@@ -1780,6 +1945,10 @@ async def get_active_tasks():
                status=progress.get("status", "downloading"),
                started_at=started_at,
                error=progress.get("error"),
+                progress=progress.get("progress"),
+                current=progress.get("current"),
+                total=progress.get("total"),
+                filename=progress.get("filename"),
            ))
    
    # Get active generations
@@ -1825,7 +1994,7 @@ async def download_cuda_backend():
            import logging
            logging.getLogger(__name__).error(f"CUDA download failed: {e}")

-    asyncio.create_task(_download())
+    _create_background_task(_download())
    return {"message": "CUDA backend download started", "progress_key": "cuda-backend"}


@@ -11,7 +11,7 @@ class VoiceProfileCreate(BaseModel):
    """Request model for creating a voice profile."""
    name: str = Field(..., min_length=1, max_length=100)
    description: Optional[str] = Field(None, max_length=500)
-    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it)$")
+    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it|he)$")


 class VoiceProfileResponse(BaseModel):
@@ -53,10 +53,11 @@ class GenerationRequest(BaseModel):
    """Request model for voice generation."""
    profile_id: str
    text: str = Field(..., min_length=1, max_length=5000)
-    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it)$")
+    language: str = Field(default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it|he)$")
    seed: Optional[int] = Field(None, ge=0)
    model_size: Optional[str] = Field(default="1.7B", pattern="^(1\\.7B|0\\.6B)$")
    instruct: Optional[str] = Field(None, max_length=500)
+    engine: Optional[str] = Field(default="qwen", pattern="^(qwen|luxtts|chatterbox)$")


 class GenerationResponse(BaseModel):
@@ -134,6 +135,7 @@ class ModelStatus(BaseModel):
    """Response model for model status."""
    model_name: str
    display_name: str
+    hf_repo_id: Optional[str] = None  # HuggingFace repository ID
    downloaded: bool
    downloading: bool = False  # True if download is in progress
    size_mb: Optional[float] = None
@@ -156,6 +158,10 @@ class ActiveDownloadTask(BaseModel):
    status: str
    started_at: datetime
    error: Optional[str] = None
+    progress: Optional[float] = None  # 0-100 percentage
+    current: Optional[int] = None     # bytes downloaded
+    total: Optional[int] = None       # total bytes
+    filename: Optional[str] = None    # current file being downloaded


 class ActiveGenerationTask(BaseModel):
@@ -38,14 +38,22 @@ async def create_profile(
 ) -> VoiceProfileResponse:
    """
    Create a new voice profile.
-    
+
    Args:
        data: Profile creation data
        db: Database session
-        
+
    Returns:
        Created profile
+
+    Raises:
+        ValueError: If a profile with the same name already exists
    """
+    # Check if profile name already exists
+    existing_profile = db.query(DBVoiceProfile).filter_by(name=data.name).first()
+    if existing_profile:
+        raise ValueError(f"A profile with the name '{data.name}' already exists. Please choose a different name.")
+
    # Create profile in database
    db_profile = DBVoiceProfile(
        id=str(uuid.uuid4()),
@@ -55,15 +63,15 @@ async def create_profile(
        created_at=datetime.utcnow(),
        updated_at=datetime.utcnow(),
    )
-    
+
    db.add(db_profile)
    db.commit()
    db.refresh(db_profile)
-    
+
    # Create profile directory
    profile_dir = _get_profiles_dir() / db_profile.id
    profile_dir.mkdir(parents=True, exist_ok=True)
-    
+
    return VoiceProfileResponse.model_validate(db_profile)


@@ -191,28 +199,37 @@ async def update_profile(
 ) -> Optional[VoiceProfileResponse]:
    """
    Update a voice profile.
-    
+
    Args:
        profile_id: Profile ID
        data: Updated profile data
        db: Database session
-        
+
    Returns:
        Updated profile or None if not found
+
+    Raises:
+        ValueError: If a profile with the same name already exists (different profile)
    """
    profile = db.query(DBVoiceProfile).filter_by(id=profile_id).first()
    if not profile:
        return None
-    
+
+    # Check if the new name conflicts with another profile
+    if profile.name != data.name:
+        existing_profile = db.query(DBVoiceProfile).filter_by(name=data.name).first()
+        if existing_profile:
+            raise ValueError(f"A profile with the name '{data.name}' already exists. Please choose a different name.")
+
    # Update fields
    profile.name = data.name
    profile.description = data.description
    profile.language = data.language
    profile.updated_at = datetime.utcnow()
-    
+
    db.commit()
    db.refresh(profile)
-    
+
    return VoiceProfileResponse.model_validate(profile)


@@ -327,6 +344,7 @@ async def create_voice_prompt_for_profile(
    profile_id: str,
    db: Session,
    use_cache: bool = True,
+    engine: str = "qwen",
 ) -> dict:
    """
    Create a combined voice prompt from all samples in a profile.
@@ -335,17 +353,20 @@ async def create_voice_prompt_for_profile(
        profile_id: Profile ID
        db: Database session
        use_cache: Whether to use cached prompts
+        engine: TTS engine to create prompt for ("qwen" or "luxtts")

    Returns:
        Voice prompt dictionary
    """
+    from .backends import get_tts_backend_for_engine
+
    # Get all samples for profile
    samples = db.query(DBProfileSample).filter_by(profile_id=profile_id).all()

    if not samples:
        raise ValueError(f"No samples found for profile {profile_id}")

-    tts_model = get_tts_model()
+    tts_model = get_tts_backend_for_engine(engine)

    if len(samples) == 1:
        # Single sample - use directly
@@ -9,11 +9,30 @@ alembic>=1.13.0

 # ML models
 torch>=2.1.0
-transformers>=4.36.0
+transformers>=4.36.0,<=4.57.6
 accelerate>=0.26.0
 huggingface_hub>=0.20.0
 qwen-tts>=0.0.5

+# LuxTTS (voice cloning engine)
+# piper-phonemize needs custom index (no PyPI wheels)
+--find-links https://k2-fsa.github.io/icefall/piper_phonemize.html
+# linacodec is a git-only dep of Zipvoice (uv-only source, pip can't resolve it)
+linacodec @ git+https://github.com/ysharma3501/LinaCodec.git
+Zipvoice @ git+https://github.com/ysharma3501/LuxTTS.git
+
+# Chatterbox TTS sub-dependencies (chatterbox-tts itself is installed
+# --no-deps in the setup script because it pins numpy<1.26 / torch==2.6
+# which are incompatible with Python 3.12+)
+conformer>=0.3.2
+diffusers>=0.29.0
+omegaconf
+pykakasi
+resemble-perth>=1.0.1
+s3tokenizer
+spacy-pkuseg
+pyloudnorm
+
 # Audio processing
 librosa>=0.10.0
 soundfile>=0.12.0
@@ -0,0 +1,217 @@
+"""
+Tests for profile duplicate name validation.
+
+This test suite verifies that the application correctly handles
+duplicate profile names and provides user-friendly error messages.
+"""
+
+import pytest
+import tempfile
+import shutil
+from pathlib import Path
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+
+# Add parent directory to path to import backend modules
+import sys
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from database import Base, VoiceProfile as DBVoiceProfile
+from models import VoiceProfileCreate
+from profiles import create_profile, update_profile
+
+
+@pytest.fixture
+def test_db():
+    """Create a temporary test database."""
+    # Create temporary directory for test database
+    temp_dir = tempfile.mkdtemp()
+    db_path = Path(temp_dir) / "test.db"
+
+    # Create engine and session
+    engine = create_engine(f"sqlite:///{db_path}")
+    Base.metadata.create_all(bind=engine)
+    SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+
+    db = SessionLocal()
+
+    yield db
+
+    # Cleanup
+    db.close()
+    shutil.rmtree(temp_dir)
+
+
+@pytest.fixture
+def mock_profiles_dir(monkeypatch, tmp_path):
+    """Mock the profiles directory to use a temporary path."""
+    import profiles
+    monkeypatch.setattr(profiles, '_get_profiles_dir', lambda: tmp_path)
+    return tmp_path
+
+
+@pytest.mark.asyncio
+async def test_create_profile_duplicate_name_raises_error(test_db, mock_profiles_dir):
+    """Test that creating a profile with a duplicate name raises a ValueError."""
+    # Create first profile
+    profile_data_1 = VoiceProfileCreate(
+        name="Test Profile",
+        description="First profile",
+        language="en"
+    )
+
+    profile_1 = await create_profile(profile_data_1, test_db)
+    assert profile_1.name == "Test Profile"
+
+    # Try to create second profile with same name
+    profile_data_2 = VoiceProfileCreate(
+        name="Test Profile",
+        description="Second profile",
+        language="en"
+    )
+
+    with pytest.raises(ValueError) as exc_info:
+        await create_profile(profile_data_2, test_db)
+
+    # Verify error message is user-friendly
+    assert "already exists" in str(exc_info.value)
+    assert "Test Profile" in str(exc_info.value)
+    assert "choose a different name" in str(exc_info.value).lower()
+
+
+@pytest.mark.asyncio
+async def test_create_profile_different_names_succeeds(test_db, mock_profiles_dir):
+    """Test that creating profiles with different names succeeds."""
+    # Create first profile
+    profile_data_1 = VoiceProfileCreate(
+        name="Profile One",
+        description="First profile",
+        language="en"
+    )
+
+    profile_1 = await create_profile(profile_data_1, test_db)
+    assert profile_1.name == "Profile One"
+
+    # Create second profile with different name
+    profile_data_2 = VoiceProfileCreate(
+        name="Profile Two",
+        description="Second profile",
+        language="en"
+    )
+
+    profile_2 = await create_profile(profile_data_2, test_db)
+    assert profile_2.name == "Profile Two"
+
+    # Verify both profiles exist
+    assert profile_1.id != profile_2.id
+
+
+@pytest.mark.asyncio
+async def test_update_profile_to_duplicate_name_raises_error(test_db, mock_profiles_dir):
+    """Test that updating a profile to a duplicate name raises a ValueError."""
+    # Create two profiles with different names
+    profile_data_1 = VoiceProfileCreate(
+        name="Profile A",
+        description="First profile",
+        language="en"
+    )
+    profile_1 = await create_profile(profile_data_1, test_db)
+
+    profile_data_2 = VoiceProfileCreate(
+        name="Profile B",
+        description="Second profile",
+        language="en"
+    )
+    profile_2 = await create_profile(profile_data_2, test_db)
+
+    # Try to update profile_2 to use profile_1's name
+    update_data = VoiceProfileCreate(
+        name="Profile A",  # Duplicate name
+        description="Updated description",
+        language="en"
+    )
+
+    with pytest.raises(ValueError) as exc_info:
+        await update_profile(profile_2.id, update_data, test_db)
+
+    # Verify error message is user-friendly
+    assert "already exists" in str(exc_info.value)
+    assert "Profile A" in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_update_profile_keep_same_name_succeeds(test_db, mock_profiles_dir):
+    """Test that updating a profile while keeping the same name succeeds."""
+    # Create profile
+    profile_data = VoiceProfileCreate(
+        name="My Profile",
+        description="Original description",
+        language="en"
+    )
+    profile = await create_profile(profile_data, test_db)
+
+    # Update profile with same name but different description
+    update_data = VoiceProfileCreate(
+        name="My Profile",  # Same name
+        description="Updated description",
+        language="en"
+    )
+
+    updated_profile = await update_profile(profile.id, update_data, test_db)
+
+    # Verify update succeeded
+    assert updated_profile is not None
+    assert updated_profile.id == profile.id
+    assert updated_profile.name == "My Profile"
+    assert updated_profile.description == "Updated description"
+
+
+@pytest.mark.asyncio
+async def test_update_profile_to_new_unique_name_succeeds(test_db, mock_profiles_dir):
+    """Test that updating a profile to a new unique name succeeds."""
+    # Create profile
+    profile_data = VoiceProfileCreate(
+        name="Original Name",
+        description="Profile description",
+        language="en"
+    )
+    profile = await create_profile(profile_data, test_db)
+
+    # Update profile with new unique name
+    update_data = VoiceProfileCreate(
+        name="New Unique Name",
+        description="Updated description",
+        language="en"
+    )
+
+    updated_profile = await update_profile(profile.id, update_data, test_db)
+
+    # Verify update succeeded
+    assert updated_profile is not None
+    assert updated_profile.id == profile.id
+    assert updated_profile.name == "New Unique Name"
+
+
+@pytest.mark.asyncio
+async def test_case_sensitive_names_allowed(test_db, mock_profiles_dir):
+    """Test that profile names are case-sensitive (e.g., 'Test' and 'test' are different)."""
+    # Create profile with lowercase name
+    profile_data_1 = VoiceProfileCreate(
+        name="test profile",
+        description="Lowercase",
+        language="en"
+    )
+    profile_1 = await create_profile(profile_data_1, test_db)
+
+    # Create profile with different case
+    profile_data_2 = VoiceProfileCreate(
+        name="Test Profile",
+        description="Title case",
+        language="en"
+    )
+    profile_2 = await create_profile(profile_data_2, test_db)
+
+    # Both should succeed since SQLite unique constraint is case-sensitive by default
+    assert profile_1.name == "test profile"
+    assert profile_2.name == "Test Profile"
+    assert profile_1.id != profile_2.id
@@ -80,6 +80,95 @@ def save_audio(
    sf.write(path, audio, sample_rate)


+def trim_tts_output(
+    audio: np.ndarray,
+    sample_rate: int = 24000,
+    frame_ms: int = 20,
+    silence_threshold_db: float = -40.0,
+    min_silence_ms: int = 200,
+    max_internal_silence_ms: int = 1000,
+    fade_ms: int = 30,
+) -> np.ndarray:
+    """
+    Trim trailing silence and post-silence hallucination from TTS output.
+
+    Chatterbox sometimes produces ``[speech][silence][hallucinated noise]``.
+    This detects internal silence gaps longer than *max_internal_silence_ms*
+    and cuts the audio at that boundary, then trims trailing silence and
+    applies a short cosine fade-out.
+
+    Args:
+        audio: Input audio array (mono float32)
+        sample_rate: Sample rate in Hz
+        frame_ms: Frame size for RMS energy calculation
+        silence_threshold_db: dB threshold below which a frame is silence
+        min_silence_ms: Minimum trailing silence to keep
+        max_internal_silence_ms: Cut after any silence gap longer than this
+        fade_ms: Cosine fade-out duration in ms
+
+    Returns:
+        Trimmed audio array
+    """
+    frame_len = int(sample_rate * frame_ms / 1000)
+    if frame_len == 0 or len(audio) < frame_len:
+        return audio
+
+    n_frames = len(audio) // frame_len
+    threshold_linear = 10 ** (silence_threshold_db / 20)
+
+    # Compute per-frame RMS
+    rms = np.array(
+        [
+            np.sqrt(np.mean(audio[i * frame_len : (i + 1) * frame_len] ** 2))
+            for i in range(n_frames)
+        ]
+    )
+    is_speech = rms >= threshold_linear
+
+    # Find first speech frame
+    first_speech = 0
+    for i, s in enumerate(is_speech):
+        if s:
+            first_speech = max(0, i - 1)  # keep 1 frame padding
+            break
+
+    # Walk forward from first speech; cut at long internal silence gaps
+    max_silence_frames = int(max_internal_silence_ms / frame_ms)
+    consecutive_silence = 0
+    cut_frame = n_frames
+
+    for i in range(first_speech, n_frames):
+        if is_speech[i]:
+            consecutive_silence = 0
+        else:
+            consecutive_silence += 1
+            if consecutive_silence >= max_silence_frames:
+                cut_frame = i - consecutive_silence + 1
+                break
+
+    # Trim trailing silence from the cut point
+    min_silence_frames = int(min_silence_ms / frame_ms)
+    end_frame = cut_frame
+    while end_frame > first_speech and not is_speech[end_frame - 1]:
+        end_frame -= 1
+    # Keep a short tail
+    end_frame = min(end_frame + min_silence_frames, cut_frame)
+
+    # Convert frames back to samples
+    start_sample = first_speech * frame_len
+    end_sample = min(end_frame * frame_len, len(audio))
+
+    trimmed = audio[start_sample:end_sample].copy()
+
+    # Cosine fade-out
+    fade_samples = int(sample_rate * fade_ms / 1000)
+    if fade_samples > 0 and len(trimmed) > fade_samples:
+        fade = np.cos(np.linspace(0, np.pi / 2, fade_samples)) ** 2
+        trimmed[-fade_samples:] *= fade
+
+    return trimmed
+
+
 def validate_reference_audio(
    audio_path: str,
    min_duration: float = 2.0,
@@ -13,7 +13,7 @@
    },
    "app": {
      "name": "@voicebox/app",
-      "version": "0.1.11",
+      "version": "0.1.12",
      "dependencies": {
        "@dnd-kit/core": "^6.3.1",
        "@dnd-kit/sortable": "^10.0.0",
@@ -68,7 +68,7 @@
    },
    "landing": {
      "name": "@voicebox/landing",
-      "version": "0.1.11",
+      "version": "0.1.12",
      "dependencies": {
        "@radix-ui/react-separator": "^1.1.8",
        "@radix-ui/react-slot": "^1.2.4",
@@ -93,7 +93,7 @@
    },
    "tauri": {
      "name": "@voicebox/tauri",
-      "version": "0.1.11",
+      "version": "0.1.12",
      "dependencies": {
        "@tauri-apps/api": "^2.0.0",
        "@tauri-apps/plugin-dialog": "^2.0.0",
@@ -116,7 +116,7 @@
    },
    "web": {
      "name": "@voicebox/web",
-      "version": "0.1.11",
+      "version": "0.1.12",
      "dependencies": {
        "@tanstack/react-query": "^5.0.0",
        "react": "^18.3.0",
@@ -125,6 +125,7 @@
        "zustand": "^4.5.0",
      },
      "devDependencies": {
+        "@tailwindcss/vite": "^4.0.0",
        "@types/react": "^18.3.0",
        "@types/react-dom": "^18.3.0",
        "@typescript-eslint/eslint-plugin": "^7.0.0",
@@ -162,7 +162,7 @@ chmod +x voicebox-*.AppImage
 **Solutions:**
 1. **Check server is running**
   ```bash
-   curl http://localhost:8000/health
+   curl http://localhost:17493/health
   ```

 2. **Check remote mode**
@@ -170,7 +170,7 @@ chmod +x voicebox-*.AppImage
   - Check firewall settings

 3. **Check port availability**
-   - Default port is 8000
+   - The current local app and dev workflow uses port 17493 by default
   - Ensure no other service is using it

 ### CORS errors in browser
@@ -276,7 +276,7 @@ chmod +x voicebox-*.AppImage

 2. **Check OpenAPI endpoint**
   ```bash
-   curl http://localhost:8000/openapi.json
+   curl http://localhost:17493/openapi.json
   ```

 3. **Regenerate client**
@@ -0,0 +1,191 @@
+# Voicebox development commands
+# Install: brew install just (or cargo install just)
+# Usage: just --list
+
+# Directories
+backend_dir := "backend"
+tauri_dir := "tauri"
+app_dir := "app"
+web_dir := "web"
+venv := backend_dir / "venv"
+venv_bin := venv / "bin"
+python := venv_bin / "python"
+pip := venv_bin / "pip"
+
+# Detect best python for venv creation
+system_python := `command -v python3.12 2>/dev/null || command -v python3.13 2>/dev/null || echo python3`
+
+# ─── Setup ────────────────────────────────────────────────────────────
+
+# Full project setup (python venv + JS deps + dev sidecar)
+setup: setup-python setup-js
+    @echo ""
+    @echo "Setup complete! Run: just dev"
+
+# Create venv and install Python dependencies
+setup-python:
+    #!/usr/bin/env bash
+    set -euo pipefail
+    if [ ! -d "{{ venv }}" ]; then
+        echo "Creating Python virtual environment..."
+        PY_MINOR=$({{ system_python }} -c "import sys; print(sys.version_info[1])")
+        if [ "$PY_MINOR" -gt 13 ]; then
+            echo "Warning: Python 3.$PY_MINOR detected. ML packages may not be compatible."
+            echo "Recommended: brew install [email protected]"
+        fi
+        {{ system_python }} -m venv {{ venv }}
+    fi
+    echo "Installing Python dependencies..."
+    {{ pip }} install --upgrade pip -q
+    {{ pip }} install -r {{ backend_dir }}/requirements.txt
+    # Chatterbox pins numpy<1.26 / torch==2.6 which break on Python 3.12+
+    {{ pip }} install --no-deps chatterbox-tts
+    # Apple Silicon: install MLX backend
+    if [ "$(uname -m)" = "arm64" ] && [ "$(uname)" = "Darwin" ]; then
+        echo "Detected Apple Silicon — installing MLX dependencies..."
+        {{ pip }} install -r {{ backend_dir }}/requirements-mlx.txt
+    fi
+    {{ pip }} install git+https://github.com/QwenLM/Qwen3-TTS.git
+    echo "Python environment ready."
+
+# Install JavaScript dependencies
+setup-js:
+    bun install
+
+# ─── Development ──────────────────────────────────────────────────────
+
+# Start backend + frontend for development (two processes, one terminal)
+dev: _ensure-venv _ensure-sidecar
+    #!/usr/bin/env bash
+    set -euo pipefail
+    trap 'kill 0' EXIT
+
+    echo "Starting backend on http://localhost:17493 ..."
+    {{ venv_bin }}/uvicorn backend.main:app --reload --port 17493 &
+    sleep 2
+
+    echo "Starting Tauri desktop app..."
+    cd {{ tauri_dir }} && bun run tauri dev &
+
+    wait
+
+# Start backend only
+dev-backend: _ensure-venv
+    {{ venv_bin }}/uvicorn backend.main:app --reload --port 17493
+
+# Start Tauri desktop app only (backend must be running separately)
+dev-frontend: _ensure-sidecar
+    cd {{ tauri_dir }} && bun run tauri dev
+
+# Start backend + web app (no Tauri)
+dev-web: _ensure-venv
+    #!/usr/bin/env bash
+    set -euo pipefail
+    trap 'kill 0' EXIT
+    {{ venv_bin }}/uvicorn backend.main:app --reload --port 17493 &
+    sleep 2
+    cd {{ web_dir }} && bun run dev &
+    wait
+
+# Kill all dev processes
+kill:
+    -pkill -f "uvicorn backend.main:app" 2>/dev/null || true
+    -pkill -f "vite" 2>/dev/null || true
+    @echo "Dev processes killed."
+
+# ─── Build ────────────────────────────────────────────────────────────
+
+# Build everything (server binary + desktop app)
+build: build-server build-tauri
+
+# Build Python server binary
+build-server: _ensure-venv
+    PATH="{{ venv_bin }}:$PATH" ./scripts/build-server.sh
+
+# Build Tauri desktop app
+build-tauri:
+    cd {{ tauri_dir }} && bun run tauri build
+
+# Build web app
+build-web:
+    cd {{ web_dir }} && bun run build
+
+# ─── Code Quality ────────────────────────────────────────────────────
+
+# Run all checks (lint + format + typecheck)
+check:
+    bun run check
+
+# Lint with Biome
+lint:
+    bun run lint
+
+# Format with Biome
+format:
+    bun run format
+
+# Fix lint + format issues
+fix:
+    bun run check:fix
+
+# ─── Database ─────────────────────────────────────────────────────────
+
+# Initialize SQLite database
+db-init: _ensure-venv
+    cd {{ backend_dir }} && {{ python }} -c "from database import init_db; init_db()"
+
+# Reset database (delete + reinit)
+db-reset:
+    rm -f {{ backend_dir }}/data/voicebox.db
+    just db-init
+
+# ─── Utilities ────────────────────────────────────────────────────────
+
+# Generate TypeScript API client (backend must be running)
+generate-api:
+    ./scripts/generate-api.sh
+
+# Open API docs in browser
+docs:
+    open http://localhost:17493/docs 2>/dev/null || xdg-open http://localhost:17493/docs
+
+# Tail backend logs
+logs:
+    tail -f {{ backend_dir }}/logs/*.log 2>/dev/null || echo "No log files found"
+
+# ─── Clean ────────────────────────────────────────────────────────────
+
+# Clean build artifacts
+clean:
+    rm -rf {{ tauri_dir }}/src-tauri/target/release
+    rm -rf {{ web_dir }}/dist
+    rm -rf {{ app_dir }}/dist
+
+# Clean Python venv and cache
+clean-python:
+    rm -rf {{ venv }}
+    find {{ backend_dir }} -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
+
+# Nuclear clean (everything including node_modules)
+clean-all: clean clean-python
+    rm -rf node_modules
+    rm -rf {{ app_dir }}/node_modules
+    rm -rf {{ tauri_dir }}/node_modules
+    rm -rf {{ web_dir }}/node_modules
+    cd {{ tauri_dir }}/src-tauri && cargo clean
+
+# ─── Internal ─────────────────────────────────────────────────────────
+
+# Ensure venv exists (prompt to run setup if not)
+[private]
+_ensure-venv:
+    #!/usr/bin/env bash
+    if [ ! -d "{{ venv }}" ]; then
+        echo "Python venv not found. Run: just setup"
+        exit 1
+    fi
+
+# Ensure Tauri dev sidecar placeholder exists
+[private]
+_ensure-sidecar:
+    bun run setup:dev
@@ -6,7 +6,7 @@ set -e
 echo "Generating OpenAPI client..."

 # Check if backend is running
-if ! curl -s http://localhost:8000/openapi.json > /dev/null 2>&1; then
+if ! curl -s http://localhost:17493/openapi.json > /dev/null 2>&1; then
    echo "Backend not running. Starting backend..."
    cd backend
    
@@ -26,19 +26,19 @@ if ! curl -s http://localhost:8000/openapi.json > /dev/null 2>&1; then
    
    # Start backend in background
    echo "Starting backend server..."
-    uvicorn main:app --port 8000 &
+    uvicorn main:app --port 17493 &  # Keep the generator on the app's documented local backend port.
    BACKEND_PID=$!
    
    # Wait for server to be ready
    echo "Waiting for server to start..."
-    for i in {1..30}; do
-        if curl -s http://localhost:8000/openapi.json > /dev/null 2>&1; then
+    for _ in {1..30}; do
+        if curl -s http://localhost:17493/openapi.json > /dev/null 2>&1; then
            break
        fi
        sleep 1
    done
    
-    if ! curl -s http://localhost:8000/openapi.json > /dev/null 2>&1; then
+    if ! curl -s http://localhost:17493/openapi.json > /dev/null 2>&1; then
        echo "Error: Backend failed to start"
        kill $BACKEND_PID 2>/dev/null || true
        exit 1
@@ -52,7 +52,7 @@ fi

 # Download OpenAPI schema
 echo "Downloading OpenAPI schema..."
-curl -s http://localhost:8000/openapi.json > app/openapi.json
+curl -s http://localhost:17493/openapi.json > app/openapi.json

 # Check if openapi-typescript-codegen is installed
 if ! bunx --bun openapi-typescript-codegen --version > /dev/null 2>&1; then
@@ -1,4 +1,5 @@
 #!/usr/bin/env node
+
 /**
 * Creates placeholder sidecar binaries for development mode.
 *
@@ -9,10 +10,10 @@
 * The actual server should be started separately with `bun run dev:server`.
 */

-import { existsSync, mkdirSync, writeFileSync, statSync } from 'fs';
-import { join, dirname } from 'path';
-import { fileURLToPath } from 'url';
 import { execSync } from 'child_process';
+import { existsSync, mkdirSync, statSync, writeFileSync } from 'fs';
+import { dirname, join } from 'path';
+import { fileURLToPath } from 'url';

 const __filename = fileURLToPath(import.meta.url);
 const __dirname = dirname(__filename);
@@ -55,7 +56,9 @@ function createPlaceholderBinary(targetTriple) {
    try {
      const stats = statSync(binaryPath);
      if (stats.size > MIN_REAL_BINARY_SIZE) {
-        console.log(`Real binary already exists: ${binaryName} (${(stats.size / 1024 / 1024).toFixed(1)} MB)`);
+        console.log(
+          `Real binary already exists: ${binaryName} (${(stats.size / 1024 / 1024).toFixed(1)} MB)`,
+        );
        return;
      }
    } catch {
@@ -73,52 +76,275 @@ function createPlaceholderBinary(targetTriple) {
    // This is the smallest valid PE that Windows will accept
    const minimalPE = Buffer.from([
      // DOS Header
-      0x4D, 0x5A, 0x90, 0x00, 0x03, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0x00, 0x00,
-      0xB8, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00,
+      0x4d,
+      0x5a,
+      0x90,
+      0x00,
+      0x03,
+      0x00,
+      0x00,
+      0x00,
+      0x04,
+      0x00,
+      0x00,
+      0x00,
+      0xff,
+      0xff,
+      0x00,
+      0x00,
+      0xb8,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x40,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x80,
+      0x00,
+      0x00,
+      0x00,
      // DOS Stub
-      0x0E, 0x1F, 0xBA, 0x0E, 0x00, 0xB4, 0x09, 0xCD, 0x21, 0xB8, 0x01, 0x4C, 0xCD, 0x21, 0x54, 0x68,
-      0x69, 0x73, 0x20, 0x70, 0x72, 0x6F, 0x67, 0x72, 0x61, 0x6D, 0x20, 0x63, 0x61, 0x6E, 0x6E, 0x6F,
-      0x74, 0x20, 0x62, 0x65, 0x20, 0x72, 0x75, 0x6E, 0x20, 0x69, 0x6E, 0x20, 0x44, 0x4F, 0x53, 0x20,
-      0x6D, 0x6F, 0x64, 0x65, 0x2E, 0x0D, 0x0D, 0x0A, 0x24, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+      0x0e,
+      0x1f,
+      0xba,
+      0x0e,
+      0x00,
+      0xb4,
+      0x09,
+      0xcd,
+      0x21,
+      0xb8,
+      0x01,
+      0x4c,
+      0xcd,
+      0x21,
+      0x54,
+      0x68,
+      0x69,
+      0x73,
+      0x20,
+      0x70,
+      0x72,
+      0x6f,
+      0x67,
+      0x72,
+      0x61,
+      0x6d,
+      0x20,
+      0x63,
+      0x61,
+      0x6e,
+      0x6e,
+      0x6f,
+      0x74,
+      0x20,
+      0x62,
+      0x65,
+      0x20,
+      0x72,
+      0x75,
+      0x6e,
+      0x20,
+      0x69,
+      0x6e,
+      0x20,
+      0x44,
+      0x4f,
+      0x53,
+      0x20,
+      0x6d,
+      0x6f,
+      0x64,
+      0x65,
+      0x2e,
+      0x0d,
+      0x0d,
+      0x0a,
+      0x24,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
      // PE Signature
-      0x50, 0x45, 0x00, 0x00,
+      0x50,
+      0x45,
+      0x00,
+      0x00,
      // COFF Header (x64)
-      0x64, 0x86, // Machine: AMD64
-      0x01, 0x00, // NumberOfSections: 1
-      0x00, 0x00, 0x00, 0x00, // TimeDateStamp
-      0x00, 0x00, 0x00, 0x00, // PointerToSymbolTable
-      0x00, 0x00, 0x00, 0x00, // NumberOfSymbols
-      0xF0, 0x00, // SizeOfOptionalHeader
-      0x22, 0x00, // Characteristics: EXECUTABLE_IMAGE | LARGE_ADDRESS_AWARE
+      0x64,
+      0x86, // Machine: AMD64
+      0x01,
+      0x00, // NumberOfSections: 1
+      0x00,
+      0x00,
+      0x00,
+      0x00, // TimeDateStamp
+      0x00,
+      0x00,
+      0x00,
+      0x00, // PointerToSymbolTable
+      0x00,
+      0x00,
+      0x00,
+      0x00, // NumberOfSymbols
+      0xf0,
+      0x00, // SizeOfOptionalHeader
+      0x22,
+      0x00, // Characteristics: EXECUTABLE_IMAGE | LARGE_ADDRESS_AWARE
      // Optional Header (PE32+)
-      0x0B, 0x02, // Magic: PE32+
-      0x00, 0x00, // Linker version
-      0x00, 0x00, 0x00, 0x00, // SizeOfCode
-      0x00, 0x00, 0x00, 0x00, // SizeOfInitializedData
-      0x00, 0x00, 0x00, 0x00, // SizeOfUninitializedData
-      0x00, 0x10, 0x00, 0x00, // AddressOfEntryPoint
-      0x00, 0x00, 0x00, 0x00, // BaseOfCode
-      0x00, 0x00, 0x00, 0x40, 0x01, 0x00, 0x00, 0x00, // ImageBase
-      0x00, 0x10, 0x00, 0x00, // SectionAlignment
-      0x00, 0x02, 0x00, 0x00, // FileAlignment
-      0x06, 0x00, 0x00, 0x00, // OS version
-      0x00, 0x00, 0x00, 0x00, // Image version
-      0x06, 0x00, 0x00, 0x00, // Subsystem version
-      0x00, 0x00, 0x00, 0x00, // Win32VersionValue
-      0x00, 0x20, 0x00, 0x00, // SizeOfImage
-      0x00, 0x02, 0x00, 0x00, // SizeOfHeaders
-      0x00, 0x00, 0x00, 0x00, // CheckSum
-      0x03, 0x00, // Subsystem: CONSOLE
-      0x60, 0x01, // DllCharacteristics
+      0x0b,
+      0x02, // Magic: PE32+
+      0x00,
+      0x00, // Linker version
+      0x00,
+      0x00,
+      0x00,
+      0x00, // SizeOfCode
+      0x00,
+      0x00,
+      0x00,
+      0x00, // SizeOfInitializedData
+      0x00,
+      0x00,
+      0x00,
+      0x00, // SizeOfUninitializedData
+      0x00,
+      0x10,
+      0x00,
+      0x00, // AddressOfEntryPoint
+      0x00,
+      0x00,
+      0x00,
+      0x00, // BaseOfCode
+      0x00,
+      0x00,
+      0x00,
+      0x40,
+      0x01,
+      0x00,
+      0x00,
+      0x00, // ImageBase
+      0x00,
+      0x10,
+      0x00,
+      0x00, // SectionAlignment
+      0x00,
+      0x02,
+      0x00,
+      0x00, // FileAlignment
+      0x06,
+      0x00,
+      0x00,
+      0x00, // OS version
+      0x00,
+      0x00,
+      0x00,
+      0x00, // Image version
+      0x06,
+      0x00,
+      0x00,
+      0x00, // Subsystem version
+      0x00,
+      0x00,
+      0x00,
+      0x00, // Win32VersionValue
+      0x00,
+      0x20,
+      0x00,
+      0x00, // SizeOfImage
+      0x00,
+      0x02,
+      0x00,
+      0x00, // SizeOfHeaders
+      0x00,
+      0x00,
+      0x00,
+      0x00, // CheckSum
+      0x03,
+      0x00, // Subsystem: CONSOLE
+      0x60,
+      0x01, // DllCharacteristics
      // Stack/Heap sizes (8 bytes each for PE32+)
-      0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x00, 0x00, // LoaderFlags
-      0x10, 0x00, 0x00, 0x00, // NumberOfRvaAndSizes
+      0x00,
+      0x00,
+      0x10,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x10,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00,
+      0x00, // LoaderFlags
+      0x10,
+      0x00,
+      0x00,
+      0x00, // NumberOfRvaAndSizes
    ]);

    // Pad to 512 bytes minimum for valid PE
@@ -138,19 +364,8 @@ exit 1
 }

 function main() {
-  console.log('Setting up development sidecar...');
-  console.log('');
-
  const targetTriple = getTargetTriple();
-  console.log(`Platform: ${targetTriple}`);
-
  createPlaceholderBinary(targetTriple);
-
-  console.log('');
-  console.log('Sidecar setup complete.');
-  console.log('For development, start the Python server in a separate terminal:');
-  console.log('  bun run dev:server');
-  console.log('');
 }

 main();
@@ -0,0 +1,382 @@
+#!/usr/bin/env python3
+"""
+Test script to observe exactly how HuggingFace reports download progress
+for each TTS model. Doesn't load models — just downloads and tracks tqdm.
+
+Usage:
+    backend/venv/bin/python scripts/test_download_progress.py qwen
+    backend/venv/bin/python scripts/test_download_progress.py luxtts
+    backend/venv/bin/python scripts/test_download_progress.py chatterbox
+
+Add --delete to clear cache first and force a real download:
+    backend/venv/bin/python scripts/test_download_progress.py chatterbox --delete
+"""
+
+import os
+import shutil
+import sys
+import time
+import threading
+from pathlib import Path
+from contextlib import contextmanager
+
+# ─── Configuration ────────────────────────────────────────────────────────────
+
+MODELS = {
+    "qwen": {
+        "repo_id": "Qwen/Qwen3-TTS-12Hz-1.7B-Base",
+        "method": "from_pretrained",
+        "description": "Qwen TTS 1.7B (uses transformers from_pretrained)",
+    },
+    "luxtts": {
+        "repo_id": "YatharthS/LuxTTS",
+        "method": "snapshot_download",
+        "description": "LuxTTS (uses snapshot_download)",
+    },
+    "chatterbox": {
+        "repo_id": "ResembleAI/chatterbox",
+        "method": "snapshot_download",
+        "allow_patterns": [
+            "ve.pt",
+            "t3_mtl23ls_v2.safetensors",
+            "s3gen.pt",
+            "grapheme_mtl_merged_expanded_v1.json",
+            "conds.pt",
+            "Cangjie5_TC.json",
+        ],
+        "description": "Chatterbox Multilingual (uses snapshot_download with allow_patterns)",
+    },
+}
+
+
+# ─── Progress tracking (mirrors our HFProgressTracker) ────────────────────────
+
+class ProgressSpy:
+    """Intercepts tqdm to see exactly what HF reports."""
+
+    def __init__(self):
+        self._lock = threading.Lock()
+        self.events = []  # List of dicts: {time, type, ...}
+        self._original_tqdm_class = None
+        self._original_tqdm_auto = None
+        self._patched_modules = {}
+        self._hf_tqdm_original_update = None
+        self._start_time = None
+
+    def _elapsed(self):
+        return time.time() - self._start_time if self._start_time else 0
+
+    def _log(self, event_type, **kwargs):
+        entry = {"time": f"{self._elapsed():.1f}s", "type": event_type, **kwargs}
+        self.events.append(entry)
+
+        # Live print
+        parts = [f"[{entry['time']:>7s}] {event_type:>10s}"]
+        for k, v in kwargs.items():
+            if k in ("current", "total") and isinstance(v, (int, float)) and v > 1_000_000:
+                parts.append(f"{k}={v / 1_000_000:.1f}MB")
+            else:
+                parts.append(f"{k}={v}")
+        print("  ".join(parts), flush=True)
+
+    def _create_tracked_tqdm_class(self):
+        spy = self
+        original_tqdm = self._original_tqdm_class
+
+        class SpyTqdm(original_tqdm):
+            def __init__(self, *args, **kwargs):
+                desc = kwargs.get("desc", "")
+                if not desc and args:
+                    first_arg = args[0]
+                    if isinstance(first_arg, str):
+                        desc = first_arg
+
+                filename = ""
+                if desc:
+                    if ":" in desc:
+                        filename = desc.split(":")[0].strip()
+                    else:
+                        filename = desc.strip()
+
+                # Filter out non-standard kwargs
+                tqdm_kwargs = {
+                    'iterable', 'desc', 'total', 'leave', 'file', 'ncols',
+                    'mininterval', 'maxinterval', 'miniters', 'ascii', 'disable',
+                    'unit', 'unit_scale', 'dynamic_ncols', 'smoothing',
+                    'bar_format', 'initial', 'position', 'postfix',
+                    'unit_divisor', 'write_bytes', 'lock_args', 'nrows',
+                    'colour', 'color', 'delay', 'gui', 'disable_default', 'pos',
+                }
+                filtered_kwargs = {k: v for k, v in kwargs.items() if k in tqdm_kwargs}
+
+                try:
+                    super().__init__(*args, **filtered_kwargs)
+                except TypeError:
+                    super().__init__(*args, **kwargs)
+
+                self._spy_filename = filename or "unknown"
+                total = getattr(self, "total", None)
+
+                spy._log(
+                    "INIT",
+                    filename=self._spy_filename,
+                    total=total or 0,
+                    unit=kwargs.get("unit", "?"),
+                    unit_scale=kwargs.get("unit_scale", False),
+                    disable=kwargs.get("disable", False),
+                )
+
+            def update(self, n=1):
+                result = super().update(n)
+
+                current = getattr(self, "n", 0)
+                total = getattr(self, "total", 0)
+                filename = self._spy_filename
+
+                spy._log(
+                    "UPDATE",
+                    filename=filename,
+                    n=n,
+                    current=current,
+                    total=total or 0,
+                    pct=f"{100 * current / total:.1f}%" if total else "?",
+                )
+
+                return result
+
+            def close(self):
+                spy._log("CLOSE", filename=self._spy_filename)
+                return super().close()
+
+        return SpyTqdm
+
+    @contextmanager
+    def patch(self):
+        """Context manager that patches tqdm globally — same as HFProgressTracker."""
+        self._start_time = time.time()
+
+        try:
+            import tqdm as tqdm_module
+            self._original_tqdm_class = tqdm_module.tqdm
+        except ImportError:
+            yield
+            return
+
+        tracked_tqdm = self._create_tracked_tqdm_class()
+
+        # Patch tqdm.tqdm
+        tqdm_module.tqdm = tracked_tqdm
+
+        # Patch tqdm.auto.tqdm
+        self._original_tqdm_auto = None
+        if hasattr(tqdm_module, "auto") and hasattr(tqdm_module.auto, "tqdm"):
+            self._original_tqdm_auto = tqdm_module.auto.tqdm
+            tqdm_module.auto.tqdm = tracked_tqdm
+
+        # Patch in sys.modules (same as HFProgressTracker)
+        tqdm_attr_names = ['tqdm', 'base_tqdm', 'old_tqdm']
+        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]
+                    for attr_name in tqdm_attr_names:
+                        if hasattr(module, attr_name):
+                            attr = getattr(module, attr_name)
+                            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")
+                                )
+                            )
+                            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
+
+        # Monkey-patch HF's tqdm.update (same as HFProgressTracker)
+        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
+                spy = self
+
+                def patched_update(tqdm_self, n=1):
+                    result = spy._hf_tqdm_original_update(tqdm_self, n)
+                    desc = getattr(tqdm_self, 'desc', '') or ''
+                    current = getattr(tqdm_self, 'n', 0)
+                    total = getattr(tqdm_self, 'total', 0) or 0
+
+                    spy._log(
+                        "HF_UPDATE",
+                        desc=desc,
+                        current=current,
+                        total=total,
+                        pct=f"{100 * current / total:.1f}%" if total else "?",
+                    )
+                    return result
+
+                hf_tqdm_class.update = patched_update
+                patched_count += 1
+        except (ImportError, AttributeError):
+            pass
+
+        print(f"\n=== Patched {patched_count} tqdm references ===\n", flush=True)
+
+        try:
+            yield
+        finally:
+            # Restore everything
+            import tqdm as tqdm_module
+            tqdm_module.tqdm = self._original_tqdm_class
+            if self._original_tqdm_auto:
+                tqdm_module.auto.tqdm = self._original_tqdm_auto
+            for key, (module, attr_name, original) in self._patched_modules.items():
+                try:
+                    setattr(module, attr_name, original)
+                except (AttributeError, TypeError):
+                    pass
+            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
+
+    def summary(self):
+        print("\n" + "=" * 70)
+        print("SUMMARY")
+        print("=" * 70)
+
+        inits = [e for e in self.events if e["type"] == "INIT"]
+        updates = [e for e in self.events if e["type"] in ("UPDATE", "HF_UPDATE")]
+
+        print(f"\ntqdm bars created: {len(inits)}")
+        for e in inits:
+            print(f"  - {e.get('filename', '?'):40s} total={e.get('total', '?')}")
+
+        print(f"\nTotal update calls: {len(updates)}")
+
+        # Group updates by filename
+        by_file = {}
+        for e in updates:
+            fn = e.get("filename") or e.get("desc", "unknown")
+            if fn not in by_file:
+                by_file[fn] = []
+            by_file[fn].append(e)
+
+        for fn, evts in by_file.items():
+            max_current = max(e.get("current", 0) for e in evts)
+            max_total = max(e.get("total", 0) for e in evts)
+            print(f"\n  {fn}:")
+            print(f"    updates: {len(evts)}")
+            print(f"    max current: {max_current:,}")
+            print(f"    max total:   {max_total:,}")
+            if max_total > 0 and max_current > 0:
+                print(f"    final pct:   {100 * max_current / max_total:.1f}%")
+            else:
+                print(f"    final pct:   NO PROGRESS REPORTED")
+
+
+# ─── Delete cache ─────────────────────────────────────────────────────────────
+
+def delete_cache(repo_id: str):
+    from huggingface_hub import constants as hf_constants
+    cache_dir = Path(hf_constants.HF_HUB_CACHE)
+    repo_cache = cache_dir / ("models--" + repo_id.replace("/", "--"))
+    if repo_cache.exists():
+        print(f"Deleting cache: {repo_cache}")
+        shutil.rmtree(repo_cache)
+        print("Deleted.")
+    else:
+        print(f"No cache found at {repo_cache}")
+
+
+# ─── Download functions ───────────────────────────────────────────────────────
+
+def download_qwen(spy: ProgressSpy):
+    """Mirrors how pytorch_backend.py downloads Qwen."""
+    from transformers import AutoModel
+    repo_id = MODELS["qwen"]["repo_id"]
+
+    print(f"Downloading {repo_id} via AutoModel.from_pretrained...")
+    with spy.patch():
+        # This is what Qwen3TTSModel.from_pretrained does under the hood
+        from huggingface_hub import snapshot_download
+        snapshot_download(repo_id)
+
+
+def download_luxtts(spy: ProgressSpy):
+    """Mirrors how luxtts_backend.py downloads LuxTTS."""
+    from huggingface_hub import snapshot_download
+    repo_id = MODELS["luxtts"]["repo_id"]
+
+    print(f"Downloading {repo_id} via snapshot_download...")
+    with spy.patch():
+        snapshot_download(repo_id)
+
+
+def download_chatterbox(spy: ProgressSpy):
+    """Mirrors how chatterbox_backend.py downloads Chatterbox."""
+    from huggingface_hub import snapshot_download
+    cfg = MODELS["chatterbox"]
+
+    print(f"Downloading {cfg['repo_id']} via snapshot_download with allow_patterns...")
+    with spy.patch():
+        snapshot_download(
+            repo_id=cfg["repo_id"],
+            repo_type="model",
+            revision="main",
+            allow_patterns=cfg["allow_patterns"],
+            token=os.getenv("HF_TOKEN"),
+        )
+
+
+# ─── Main ─────────────────────────────────────────────────────────────────────
+
+def main():
+    if len(sys.argv) < 2 or sys.argv[1] not in MODELS:
+        print(f"Usage: {sys.argv[0]} <{'|'.join(MODELS.keys())}> [--delete]")
+        sys.exit(1)
+
+    model_key = sys.argv[1]
+    should_delete = "--delete" in sys.argv
+    cfg = MODELS[model_key]
+
+    print(f"\n{'=' * 70}")
+    print(f"Testing download progress for: {cfg['description']}")
+    print(f"Repo: {cfg['repo_id']}")
+    print(f"Method: {cfg['method']}")
+    print(f"{'=' * 70}\n")
+
+    if should_delete:
+        delete_cache(cfg["repo_id"])
+        print()
+
+    spy = ProgressSpy()
+
+    dispatch = {
+        "qwen": download_qwen,
+        "luxtts": download_luxtts,
+        "chatterbox": download_chatterbox,
+    }
+
+    try:
+        dispatch[model_key](spy)
+    except Exception as e:
+        print(f"\n!!! Download failed: {e}")
+
+    spy.summary()
+
+
+if __name__ == "__main__":
+    main()
@@ -5041,7 +5041,7 @@ checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"

 [[package]]
 name = "voicebox"
-version = "0.1.12"
+version = "0.1.13"
 dependencies = [
 "base64 0.22.1",
 "core-foundation-sys",
@@ -5064,6 +5064,7 @@ dependencies = [
 "tauri-plugin-updater",
 "tokio",
 "wasapi",
+ "webkit2gtk",
 "windows 0.62.2",
 ]

@@ -37,6 +37,9 @@ core-foundation-sys = "0.8"
 wasapi = "0.22"
 windows = { version = "0.62", features = ["Win32_Foundation", "Win32_UI_WindowsAndMessaging", "Win32_System_Com"] }

+[target.'cfg(target_os = "linux")'.dependencies]
+webkit2gtk = "2.0"
+
 [target.'cfg(not(any(target_os = "android", target_os = "ios")))'.dependencies]
 tauri-plugin-updater = "2.0"
 tauri-plugin-process = "2.0"
@@ -714,6 +714,43 @@ pub fn run() {
                }
            }

+            // Enable microphone access on Linux (WebKitGTK denies getUserMedia by default)
+            #[cfg(target_os = "linux")]
+            {
+                use tauri::Manager;
+                if let Some(window) = app.get_webview_window("main") {
+                    let _ = window.with_webview(|webview| {
+                        use webkit2gtk::{WebViewExt, SettingsExt, PermissionRequestExt};
+                        use webkit2gtk::glib::ObjectExt;
+                        let wk_webview = webview.inner();
+
+                        // Enable media stream support in WebKitGTK settings
+                        if let Some(settings) = WebViewExt::settings(&wk_webview) {
+                            settings.set_enable_media_stream(true);
+                        }
+
+                        // Auto-grant UserMediaPermissionRequest (microphone access)
+                        // Only for trusted local origins (Tauri dev server or custom protocol)
+                        wk_webview.connect_permission_request(move |webview, request: &webkit2gtk::PermissionRequest| {
+                            if request.is::<webkit2gtk::UserMediaPermissionRequest>() {
+                                let uri = WebViewExt::uri(webview).unwrap_or_default();
+                                let is_trusted = uri.starts_with("tauri://")
+                                    || uri.starts_with("https://tauri.localhost")
+                                    || uri.starts_with("http://localhost")
+                                    || uri.starts_with("http://127.0.0.1");
+                                if is_trusted {
+                                    request.allow();
+                                    return true;
+                                }
+                                request.deny();
+                                return true;
+                            }
+                            false
+                        });
+                    });
+                }
+            }
+
            Ok(())
        })
        .invoke_handler(tauri::generate_handler![
Author	SHA1	Message	Date
James Pine	53f640a027	merge: resolve conflicts with latest main	2026-03-13 02:41:28 -07:00
Jamie PineandGitHub	3e6513c0fb	Merge pull request #257 from jamiepine/feat/chatterbox feat: Chatterbox TTS engine with multilingual voice cloning	2026-03-13 02:12:56 -07:00
James Pine	c54ee14173	fix: model loaded icon uses accent-colored CircleCheck, show size for loaded models, fix generate box overlapping player on stories route	2026-03-13 02:09:32 -07:00
James Pine	cc07d4d3c9	fix: download progress tracking for all engines and inline progress UI - Add HFProgressTracker to LuxTTS and Chatterbox backends so tqdm-based file-level download progress reaches the frontend (previously only Qwen had this, LuxTTS/Chatterbox showed a static spinner) - Add progress/current/total/filename fields to ActiveDownloadTask so the /tasks/active polling endpoint carries progress data - Show inline progress bar + bytes in the model list and detail modal, poll at 1s during active downloads (5s otherwise) - Fix GpuAcceleration crash: cudaStatusLoading was referenced before initialization in its own useQuery declaration	2026-03-13 02:09:32 -07:00
James Pine	9beb9d7fec	fix: install chatterbox-tts with --no-deps to avoid numpy pin conflict chatterbox-tts 0.1.6 pins numpy<1.26 and torch==2.6 which are incompatible with Python 3.12+. Install with --no-deps and list its sub-dependencies explicitly in requirements.txt. Also removes HFProgressTracker from chatterbox backend to avoid 'generator didn't stop after throw()' errors from tqdm patching.	2026-03-13 02:09:32 -07:00
James Pine	76bb207b2b	feat: add Chatterbox TTS engine for multilingual voice cloning - New ChatterboxTTSBackend wrapping ChatterboxMultilingualTTS (ResembleAI/chatterbox) - Supports 23 languages including Hebrew, forces CPU on macOS (MPS issue) - Monkey-patches torch.load for CPU loading, forces eager attention for compatibility - trim_tts_output utility cuts trailing silence/hallucination from Chatterbox output - Full engine integration: /generate, /generate/stream, model status/download/delete - Hebrew (he) added to supported languages in frontend and backend validation - Single flat model dropdown extended with Chatterbox option in both generation UIs - ModelManagement UI groups LuxTTS and Chatterbox under 'Other Voice Models' section	2026-03-13 02:09:32 -07:00
Jamie PineandGitHub	3576521d62	Merge pull request #254 from jamiepine/feat/luxtts feat: LuxTTS integration — multi-engine TTS support	2026-03-13 02:04:46 -07:00
Jamie PineandGitHub	2df4ece388	Merge pull request #210 from ieguiguren/fix/linux-nvidia-gbm-buffer fix: Linux NVIDIA GBM buffer crash + WebKitGTK microphone access	2026-03-13 01:55:58 -07:00
Jamie PineandGitHub	cbb4979ed6	Merge pull request #175 from Vaibhavee89/fix/profile-duplicate-name-validation Fix #134: Add validation for duplicate profile names	2026-03-13 01:55:30 -07:00
James Pine	753158c1c9	fix: address review feedback — race condition, GPU safety, task GC - Add threading lock to get_tts_backend_for_engine() to prevent race condition where concurrent requests could create duplicate backend instances (double-checked locking pattern) - Fix LuxTTS generate: call .detach().cpu() before .numpy() so it works on GPU/MPS devices, not just CPU - Store background download tasks in a module-level set to prevent garbage collection before completion (asyncio.create_task fire-and- forget pattern) - Deduplicate cache_key computation in LuxTTS create_voice_prompt - Prefix unused sr variable with underscore	2026-03-13 01:54:09 -07:00
Jamie PineandGitHub	573f82a7e6	Merge pull request #250 from pandego/fix/docs-align-local-port-17493 docs: align local API port examples with current dev flow	2026-03-13 01:53:28 -07:00
James Pine	1e5afc2bef	fix: LuxTTS generation and preserve model selection after generate - Fix silent Zod validation failure when LuxTTS selected (modelSize was set to 'default' which failed enum validation, preventing form submit) - Preserve engine, model size, and language after successful generation instead of resetting to defaults	2026-03-13 00:21:43 -07:00
James Pine	163528bf69	fix: single flat model dropdown, linacodec dep, quiet sidecar script - Combine engine + model size into one flat dropdown (Qwen3-TTS 1.7B, Qwen3-TTS 0.6B, LuxTTS) in both FloatingGenerateBox and GenerationForm - Add linacodec git dep to requirements.txt (uv-only source, pip can't resolve it from Zipvoice's pyproject.toml) - Remove redundant transitive deps from requirements.txt - Quiet the sidecar setup script (was printing misleading instructions)	2026-03-13 00:21:43 -07:00
James Pine	e1ad7a6e73	fix: add piper-phonemize find-links for LuxTTS install piper-phonemize has no PyPI wheels — needs custom find-links URL from k2-fsa.github.io. Removed redundant transitive deps that Zipvoice already declares.	2026-03-13 00:21:43 -07:00
James Pine	411e91bb19	docs: add just commands to README dev quick start	2026-03-13 00:21:43 -07:00
James Pine	05cf163744	chore: add justfile for streamlined dev setup and workflow Adds 'just' as the recommended dev tool: 'just setup' for one-time install, 'just dev' to run backend + frontend in one terminal. Updates CONTRIBUTING.md to document just as the primary setup method.	2026-03-13 00:21:43 -07:00
James Pine	d46eb5bcc6	feat: add LuxTTS as second TTS engine with multi-engine support Introduce LuxTTS (ZipVoice) alongside Qwen TTS, enabling users to choose between engines at generation time. LuxTTS offers fast, English-focused voice cloning at 48kHz with ~1GB VRAM. Backend: - Add LuxTTSBackend with encode_prompt/generate_speech integration - Multi-engine registry (get_tts_backend_for_engine) replacing singleton - Engine-prefixed voice prompt cache keys to avoid collisions - Engine field on GenerationRequest (default 'qwen' for backward compat) - Engine dispatch in /generate and /generate/stream endpoints - LuxTTS in model status, download, and delete maps Frontend: - TTS Engine selector dropdown in GenerationForm (Qwen TTS / LuxTTS) - Conditionally hide Model Size and Delivery Instructions for LuxTTS - Engine field added to TypeScript types and Zod schema - LuxTTS section in Model Management page	2026-03-13 00:21:43 -07:00
Jamie PineandGitHub	6359dee406	Merge pull request #252 from jamiepine/feat/cuda-backend-swap feat: CUDA backend swap via binary download and restart	2026-03-13 00:20:40 -07:00
pandego	3d2506767d	docs: address review nits for API generator	2026-03-13 05:08:25 +01:00
pandego	cdef2163c1	docs: align local API port examples with current dev flow	2026-03-12 12:17:50 +01:00
IvanandClaude Opus 4.6	30ee07c2e3	fix: scope DMABUF workaround to Linux+NVIDIA, add origin validation Address CodeRabbit review feedback: - Makefile: only set WEBKIT_DISABLE_DMABUF_RENDERER=1 when running on Linux with an NVIDIA GPU detected via lspci - main.rs: validate webview origin before auto-granting microphone permission — only allow for trusted local origins (tauri://, localhost, 127.0.0.1) Co-Authored-By: Claude Opus 4.6 <[email protected]>	2026-02-27 07:01:32 +01:00
IvanandClaude Opus 4.6	d21c63b52c	fix: enable microphone access on Linux via WebKitGTK WebKitGTK denies getUserMedia by default. This adds webkit2gtk as a Linux dependency and configures the webview to enable media streams and auto-grant UserMediaPermissionRequest for microphone access. Co-Authored-By: Claude Opus 4.6 <[email protected]>	2026-02-27 06:49:08 +01:00
IvanandClaude Opus 4.6	5ad67d7ecb	fix: disable DMABUF renderer for NVIDIA GPUs on Linux WebKitGTK fails to create GBM buffers with NVIDIA proprietary drivers, resulting in an empty/blank Tauri window. Set WEBKIT_DISABLE_DMABUF_RENDERER=1 in the dev target to work around this. Co-Authored-By: Claude Opus 4.6 <[email protected]>	2026-02-27 06:32:02 +01:00
Vaibhavee Singh	6cc96c2614	Fix #134 : Add validation for duplicate profile names - Add validation in create_profile() to check for existing names before insert - Add validation in update_profile() to prevent renaming to duplicate names - Improve error handling in API endpoints with user-friendly messages - Add comprehensive test suite for duplicate name validation - Update CHANGELOG.md with fix details This fix prevents database constraint violations and provides clear error messages when users attempt to create or update profiles with names that already exist in the database.	2026-02-24 10:17:39 +05:30
Omer Celik	831a50cf61	Prepare feature branch for PR	2026-02-22 21:29:55 +00:00