Merge pull request #254 from jamiepine/feat/luxtts

feat: LuxTTS integration — multi-engine TTS support

CONTRIBUTING.md

@@ -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):**
 

README.md

@@ -228,42 +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
+just setup   # creates Python venv, installs all deps
-make setup
+just dev     # starts backend + desktop app
-
-# Start development
-make dev
 ```
 
-**Manual setup (all platforms):**
+Install [just](https://github.com/casey/just): `brew install just` or `cargo install just`. Run `just --list` to see all commands.
 
-```bash
+Also available via Makefile: `make setup && make dev` (run `make help` for all commands).
-# Clone the repo
-git clone https://github.com/jamiepine/voicebox.git
-cd voicebox
 
-# Install dependencies
+**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org), [XCode on macOS](https://developer.apple.com/xcode/).
-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/).
 
 **Performance:** 
 - **Apple Silicon (M1/M2/M3)**: Uses MLX backend with native Metal acceleration for 4-5x faster inference

app/src/components/Generation/FloatingGenerateBox.tsx

@@ -316,7 +316,7 @@ export function FloatingGenerateBox({
                   </span>
                 </div>
                 <AnimatePresence>
-                  {isExpanded && (
+                  {isExpanded && form.watch('engine') !== 'luxtts' && (
                     <motion.div
                       initial={{ opacity: 0, scale: 0.8 }}
                       animate={{ opacity: 1, scale: 1 }}
@@ -402,30 +402,41 @@ export function FloatingGenerateBox({
                     )}
                   />
 
-                  <FormField
+                  <FormItem className="flex-1 space-y-0">
-                    control={form.control}
+                    <Select
-                    name="modelSize"
+                      value={
-                    render={({ field }) => (
+                        form.watch('engine') === 'luxtts'
-                      <FormItem className="flex-1 space-y-0">
+                          ? 'luxtts'
-                        <Select onValueChange={field.onChange} defaultValue={field.value}>
+                          : `qwen:${form.watch('modelSize') || '1.7B'}`
-                          <FormControl>
+                      }
-                            <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
+                      onValueChange={(value) => {
-                              <SelectValue />
+                        if (value === 'luxtts') {
-                            </SelectTrigger>
+                          form.setValue('engine', 'luxtts');
-                          </FormControl>
+                        } else {
-                          <SelectContent>
+                          const [, modelSize] = value.split(':');
-                            <SelectItem value="1.7B" className="text-xs text-muted-foreground">
+                          form.setValue('engine', 'qwen');
-                              Qwen3-TTS 1.7B
+                          form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
-                            </SelectItem>
+                        }
-                            <SelectItem value="0.6B" className="text-xs text-muted-foreground">
+                      }}
-                              Qwen3-TTS 0.6B
+                    >
-                            </SelectItem>
+                      <FormControl>
-                          </SelectContent>
+                        <SelectTrigger className="h-8 text-xs bg-card border-border rounded-full hover:bg-background/50 transition-all">
-                        </Select>
+                          <SelectValue />
-                        <FormMessage className="text-xs" />
+                        </SelectTrigger>
-                      </FormItem>
+                      </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>
+                      </SelectContent>
+                    </Select>
+                  </FormItem>
                 </div>
               </motion.div>
             </AnimatePresence>

app/src/components/Generation/GenerationForm.tsx

@@ -76,29 +76,67 @@ export function GenerationForm() {
               )}
             />
 
-            <FormField
+            {form.watch('engine') !== 'luxtts' && (
-              control={form.control}
+              <FormField
-              name="instruct"
+                control={form.control}
-              render={({ field }) => (
+                name="instruct"
-                <FormItem>
+                render={({ field }) => (
-                  <FormLabel>Delivery Instructions (optional)</FormLabel>
+                  <FormItem>
-                  <FormControl>
+                    <FormLabel>Delivery Instructions (optional)</FormLabel>
-                    <Textarea
+                    <FormControl>
-                      placeholder="e.g. Speak slowly with emphasis, Warm and friendly tone, Professional and authoritative..."
+                      <Textarea
-                      className="min-h-[80px]"
+                        placeholder="e.g. Speak slowly with emphasis, Warm and friendly tone, Professional and authoritative..."
-                      {...field}
+                        className="min-h-[80px]"
-                    />
+                        {...field}
-                  </FormControl>
+                      />
-                  <FormDescription>
+                    </FormControl>
-                    Natural language instructions to control speech delivery (tone, emotion, pace).
+                    <FormDescription>
-                    Max 500 characters
+                      Natural language instructions to control speech delivery (tone, emotion,
-                  </FormDescription>
+                      pace). Max 500 characters
-                  <FormMessage />
+                    </FormDescription>
-                </FormItem>
+                    <FormMessage />
-              )}
+                  </FormItem>
-            />
+                )}
+              />
+            )}
 
             <div className="grid gap-4 md:grid-cols-3">
+              <FormItem>
+                <FormLabel>Model</FormLabel>
+                <Select
+                  value={
+                    form.watch('engine') === 'luxtts'
+                      ? 'luxtts'
+                      : `qwen:${form.watch('modelSize') || '1.7B'}`
+                  }
+                  onValueChange={(value) => {
+                    if (value === 'luxtts') {
+                      form.setValue('engine', 'luxtts');
+                    } 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>
+                  </SelectContent>
+                </Select>
+                <FormDescription>
+                  {form.watch('engine') === 'luxtts'
+                    ? 'Fast, English-focused'
+                    : 'Multi-language, two sizes'}
+                </FormDescription>
+              </FormItem>
+
               <FormField
                 control={form.control}
                 name="language"
@@ -124,29 +162,6 @@ 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 +185,7 @@ export function GenerationForm() {
               />
             </div>
 
-            <Button
+            <Button type="submit" className="w-full" disabled={isPending || !selectedProfileId}>
-              type="submit"
-              className="w-full"
-              disabled={isPending || !selectedProfileId}
-            >
               {isPending ? (
                 <>
                   <Loader2 className="mr-2 h-4 w-4 animate-spin" />

app/src/components/ServerSettings/ModelManagement.tsx

@@ -80,16 +80,19 @@ export function ModelManagement() {
     queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
   }, [queryClient]);
 
-  const handleDownloadError = useCallback((error: string) => {
+  const handleDownloadError = useCallback(
-    console.log('[ModelManagement] Download error, clearing state');
+    (error: string) => {
-    if (downloadingModel) {
+      console.log('[ModelManagement] Download error, clearing state');
-      setLocalErrors((prev) => new Map(prev).set(downloadingModel, error));
+      if (downloadingModel) {
-      setConsoleOpen(true);
+        setLocalErrors((prev) => new Map(prev).set(downloadingModel, error));
-    }
+        setConsoleOpen(true);
-    setDownloadingModel(null);
+      }
-    setDownloadingDisplayName(null);
+      setDownloadingModel(null);
-    queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
+      setDownloadingDisplayName(null);
-  }, [queryClient, downloadingModel]);
+      queryClient.invalidateQueries({ queryKey: ['activeTasks'] });
+    },
+    [queryClient, downloadingModel],
+  );
 
   // Use progress toast hook for the downloading model
   useModelDownloadToast({
@@ -165,7 +168,11 @@ export function ModelManagement() {
 
     // 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);
@@ -178,7 +185,11 @@ export function ModelManagement() {
         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',
+        });
       },
     });
   };
@@ -273,7 +284,9 @@ export function ModelManagement() {
                       }}
                       onCancel={() => handleCancel(model.model_name)}
                       isDownloading={downloadingModel === model.model_name}
-                      isCancelling={cancelMutation.isPending && cancelMutation.variables === 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}
@@ -282,6 +295,34 @@ export function ModelManagement() {
               </div>
             </div>
 
+            {/* LuxTTS Models */}
+            {modelStatus.models.some((m) => m.model_name.startsWith('luxtts')) && (
+              <div>
+                <h3 className="text-sm font-semibold mb-3 text-muted-foreground">LuxTTS Models</h3>
+                <div className="space-y-2">
+                  {modelStatus.models
+                    .filter((m) => m.model_name.startsWith('luxtts'))
+                    .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);
+                        }}
+                        isDownloading={downloadingModel === model.model_name}
+                        formatSize={formatSize}
+                      />
+                    ))}
+                </div>
+              </div>
+            )}
+
             {/* Whisper Models */}
             <div>
               <h3 className="text-sm font-semibold mb-3 text-muted-foreground">
@@ -305,7 +346,9 @@ export function ModelManagement() {
                       }}
                       onCancel={() => handleCancel(model.model_name)}
                       isDownloading={downloadingModel === model.model_name}
-                      isCancelling={cancelMutation.isPending && cancelMutation.variables === 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}
@@ -353,12 +396,16 @@ export function ModelManagement() {
                         {dl.error ? (
                           <>
                             {': '}
-                            <span className="text-[#ce9178] whitespace-pre-wrap break-all">{dl.error}</span>
+                            <span className="text-[#ce9178] whitespace-pre-wrap break-all">
+                              {dl.error}
+                            </span>
                           </>
                         ) : (
                           <>
                             {': '}
-                            <span className="text-[#808080]">No error details available. Try downloading again.</span>
+                            <span className="text-[#808080]">
+                              No error details available. Try downloading again.
+                            </span>
                           </>
                         )}
                         <div className="text-[#6a9955] mt-0.5">
@@ -422,21 +469,31 @@ interface ModelItemProps {
     model_name: string;
     display_name: string;
     downloaded: boolean;
-    downloading?: boolean;  // From server - true if download in progress
+    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
+  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) {
+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;

app/src/lib/api/types.ts

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

app/src/lib/hooks/useGenerationForm.ts

@@ -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']).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 +69,14 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
     try {
       setIsGenerating(true);
 
-      const modelName = `qwen-tts-${data.modelSize}`;
+      const engine = data.engine || 'qwen';
-      const displayName = data.modelSize === '1.7B' ? 'Qwen TTS 1.7B' : 'Qwen TTS 0.6B';
+      const modelName = engine === 'luxtts' ? 'luxtts' : `qwen-tts-${data.modelSize}`;
+      const displayName =
+        engine === 'luxtts'
+          ? 'LuxTTS'
+          : data.modelSize === '1.7B'
+            ? 'Qwen TTS 1.7B'
+            : 'Qwen TTS 0.6B';
 
       try {
         const modelStatus = await apiClient.getModelStatus();
@@ -87,8 +95,9 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
         text: data.text,
         language: data.language,
         seed: data.seed,
-        model_size: data.modelSize,
+        model_size: engine === 'luxtts' ? undefined : data.modelSize,
-        instruct: data.instruct || undefined,
+        engine,
+        instruct: engine === 'luxtts' ? undefined : data.instruct || undefined,
       });
 
       toast({
@@ -99,7 +108,14 @@ 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({

backend/backends/__init__.py

@@ -4,6 +4,7 @@ Backend abstraction layer for TTS and STT.
 Provides a unified interface for MLX and PyTorch backends.
 """
 
+import threading
 from typing import Protocol, Optional, Tuple, List
 from typing_extensions import runtime_checkable
 import numpy as np
@@ -112,29 +113,65 @@ 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",
+}
+
 
 def get_tts_backend() -> TTSBackend:
     """
-    Get or create TTS backend instance based on platform.
+    Get or create the default (Qwen) TTS backend instance based on platform.
     
     Returns:
         TTS backend instance (MLX or PyTorch)
     """
-    global _tts_backend
+    return get_tts_backend_for_engine("qwen")
+
+
+def get_tts_backend_for_engine(engine: str) -> TTSBackend:
+    """
+    Get or create a TTS backend for the given engine.
     
-    if _tts_backend is None:
+    Args:
-        backend_type = get_backend_type()
+        engine: Engine name ("qwen" or "luxtts")
+    
+    Returns:
+        TTS backend instance
+    """
+    global _tts_backends
+    
+    # Fast path: check without lock
+    if engine in _tts_backends:
+        return _tts_backends[engine]
+    
+    # Slow path: create with lock to avoid duplicate instantiation
+    with _tts_backends_lock:
+        # Double-check after acquiring lock
+        if engine in _tts_backends:
+            return _tts_backends[engine]
         
-        if backend_type == "mlx":
+        if engine == "qwen":
-            from .mlx_backend import MLXTTSBackend
+            backend_type = get_backend_type()
-            _tts_backend = MLXTTSBackend()
+            if backend_type == "mlx":
+                from .mlx_backend import MLXTTSBackend
+                backend = MLXTTSBackend()
+            else:
+                from .pytorch_backend import PyTorchTTSBackend
+                backend = PyTorchTTSBackend()
+        elif engine == "luxtts":
+            from .luxtts_backend import LuxTTSBackend
+            backend = LuxTTSBackend()
         else:
-            from .pytorch_backend import PyTorchTTSBackend
+            raise ValueError(f"Unknown TTS engine: {engine}. Supported: {list(TTS_ENGINES.keys())}")
-            _tts_backend = PyTorchTTSBackend()
+        
-    
+        _tts_backends[engine] = backend
-    return _tts_backend
+        return backend
 
 
 def get_stt_backend() -> STTBackend:
@@ -161,6 +198,7 @@ def get_stt_backend() -> STTBackend:
 
 def reset_backends():
     """Reset backend instances (useful for testing)."""
-    global _tts_backend, _stt_backend
+    global _tts_backend, _tts_backends, _stt_backend
     _tts_backend = None
+    _tts_backends.clear()
     _stt_backend = None

backend/backends/luxtts_backend.py

@@ -0,0 +1,264 @@
+"""
+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."""
+        progress_manager = get_progress_manager()
+        task_manager = get_task_manager()
+        model_name = "luxtts"
+
+        is_cached = self._is_model_cached()
+
+        if not is_cached:
+            task_manager.start_download(model_name)
+            progress_manager.update_progress(
+                model_name=model_name,
+                current=0,
+                total=0,
+                filename="Downloading LuxTTS model...",
+                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
+            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,
+                )
+
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
+
+            logger.info("LuxTTS loaded successfully")
+
+        except Exception as e:
+            logger.error(f"Failed to load LuxTTS: {e}")
+            if not is_cached:
+                progress_manager.mark_error(model_name, str(e))
+                task_manager.error_download(model_name, str(e))
+            raise
+
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        if self.model is not None:
+            del self.model
+            self.model = None
+
+            import torch
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+
+            logger.info("LuxTTS unloaded")
+
+    async def create_voice_prompt(
+        self,
+        audio_path: str,
+        reference_text: str,
+        use_cache: bool = True,
+    ) -> Tuple[dict, bool]:
+        """
+        Create voice prompt from reference audio.
+
+        LuxTTS uses its own encode_prompt() which runs Whisper ASR internally
+        to transcribe the reference. The reference_text parameter is not used
+        by LuxTTS itself, but we include it in the cache key for consistency.
+        """
+        await self.load_model()
+
+        # Compute cache key once for both lookup and storage
+        cache_key = ("luxtts_" + get_cache_key(audio_path, reference_text)) if use_cache else None
+
+        if cache_key:
+            cached = get_cached_voice_prompt(cache_key)
+            if cached is not None and isinstance(cached, dict):
+                return cached, True
+
+        def _encode_sync():
+            return self.model.encode_prompt(
+                prompt_audio=str(audio_path),
+                duration=5,
+                rms=0.01,
+            )
+
+        encoded = await asyncio.to_thread(_encode_sync)
+
+        if cache_key:
+            cache_voice_prompt(cache_key, encoded)
+
+        return encoded, False
+
+    async def combine_voice_prompts(
+        self,
+        audio_paths: List[str],
+        reference_texts: List[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple reference samples.
+
+        LuxTTS doesn't have native multi-prompt support, so we concatenate
+        the audio and let encode_prompt handle the combined clip.
+        """
+        combined_audio = []
+        for path in audio_paths:
+            audio, _sr = load_audio(path, sample_rate=24000)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        combined_text = " ".join(reference_texts)
+
+        return mixed, combined_text
+
+    async def generate(
+        self,
+        text: str,
+        voice_prompt: dict,
+        language: str = "en",
+        seed: Optional[int] = None,
+        instruct: Optional[str] = None,
+    ) -> Tuple[np.ndarray, int]:
+        """
+        Generate audio from text using LuxTTS.
+
+        Args:
+            text: Text to synthesize
+            voice_prompt: Encoded prompt dict from encode_prompt()
+            language: Language code (LuxTTS is English-focused)
+            seed: Random seed for reproducibility
+            instruct: Not supported by LuxTTS (ignored)
+
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        await self.load_model()
+
+        def _generate_sync():
+            import torch
+
+            if seed is not None:
+                torch.manual_seed(seed)
+                if torch.cuda.is_available():
+                    torch.cuda.manual_seed(seed)
+
+            wav = self.model.generate_speech(
+                text=text,
+                encode_dict=voice_prompt,
+                num_steps=4,
+                guidance_scale=3.0,
+                t_shift=0.5,
+                speed=1.0,
+                return_smooth=False,  # 48kHz output
+            )
+
+            # LuxTTS returns a tensor (may be on GPU/MPS), move to CPU first
+            audio = wav.detach().cpu().numpy().squeeze()
+            return audio, 48000
+
+        return await asyncio.to_thread(_generate_sync)

backend/main.py

@@ -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",
@@ -608,47 +620,69 @@ 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.
+        engine = data.engine or "qwen"
-        # This must happen before create_voice_prompt_for_profile because that
+        tts_model = get_tts_backend_for_engine(engine)
-        # 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
+        # Resolve model size (only relevant for Qwen engine)
-        # returns immediately and the voice prompt is created by the correct model.
-        tts_model = tts.get_tts_model()
         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 engine == "qwen":
-        if not tts_model._is_model_cached(model_size):
+            if not tts_model._is_model_cached(model_size):
-            # Model is not fully cached — kick off a background download and tell
+                model_name = f"qwen-tts-{model_size}"
-            # the client to retry once it's ready.
-            model_name = f"qwen-tts-{model_size}"
 
-            async def download_model_background():
+                async def download_model_background():
-                try:
+                    try:
-                    await tts_model.load_model_async(model_size)
+                        await tts_model.load_model_async(model_size)
-                except Exception as e:
+                    except Exception as e:
-                    task_manager.error_download(model_name, str(e))
+                        task_manager.error_download(model_name, str(e))
 
-            task_manager.start_download(model_name)
+                task_manager.start_download(model_name)
-            asyncio.create_task(download_model_background())
+                _create_background_task(download_model_background())
 
-            raise HTTPException(
+                raise HTTPException(
-                status_code=202,
+                    status_code=202,
-                detail={
+                    detail={
-                    "message": f"Model {model_size} is being downloaded. Please wait and try again.",
+                        "message": f"Model {model_size} is being downloaded. Please wait and try again.",
-                    "model_name": model_name,
+                        "model_name": model_name,
-                    "downloading": True,
+                        "downloading": True,
-                },
+                    },
-            )
+                )
 
-        # Load (or switch to) the requested model before building the voice prompt
+            # Load (or switch to) the requested model
-        await tts_model.load_model_async(model_size)
+            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()
+
+        # 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(
@@ -705,23 +739,34 @@ 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):
+    if engine == "qwen":
-        raise HTTPException(
+        if not tts_model._is_model_cached(model_size):
-            status_code=400,
+            raise HTTPException(
-            detail=f"Model {model_size} is not downloaded yet. Use /generate to trigger a download.",
+                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()
 
-    # Load the correct model before building the voice prompt (fixes issue #96)
+    voice_prompt = await profiles.create_voice_prompt_for_profile(
-    await tts_model.load_model_async(model_size)
+        data.profile_id, db, engine=engine,
-
+    )
-    voice_prompt = await profiles.create_voice_prompt_for_profile(data.profile_id, db)
 
     audio, sample_rate = await tts_model.generate(
         data.text,
@@ -959,7 +1004,7 @@ 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(
@@ -1330,6 +1375,15 @@ 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
+
     model_configs = [
         {
             "model_name": "qwen-tts-1.7B",
@@ -1345,6 +1399,13 @@ 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": "whisper-base",
             "display_name": "Whisper Base",
@@ -1527,6 +1588,7 @@ 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()
@@ -1540,6 +1602,10 @@ 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(),
+        },
         "whisper-base": {
             "model_size": "base",
             "load_func": lambda: transcribe.get_whisper_model().load_model("base"),
@@ -1591,7 +1657,7 @@ 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"}
@@ -1652,6 +1718,11 @@ 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",
+        },
         "whisper-base": {
             "hf_repo_id": "openai/whisper-base",
             "model_size": "base",
@@ -1686,6 +1757,11 @@ 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"] == "whisper":
             whisper_model = transcribe.get_whisper_model()
             if whisper_model.is_loaded() and whisper_model.model_size == config["model_size"]:
@@ -1831,7 +1907,7 @@ 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"}
 
 

backend/models.py

@@ -57,6 +57,7 @@ class GenerationRequest(BaseModel):
     seed: Optional[int] = Field(None, ge=0)
     model_size: Optional[str] = Field(default="1.7B", pattern="^(1\\.7B|0\\.6B)$")
     instruct: Optional[str] = Field(None, max_length=500)
+    engine: Optional[str] = Field(default="qwen", pattern="^(qwen|luxtts)$")
 
 
 class GenerationResponse(BaseModel):

backend/profiles.py

@@ -344,6 +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.
@@ -352,17 +353,20 @@ async def create_voice_prompt_for_profile(
         profile_id: Profile ID
         db: Database session
         use_cache: Whether to use cached prompts
+        engine: TTS engine to create prompt for ("qwen" or "luxtts")
 
     Returns:
         Voice prompt dictionary
     """
+    from .backends import get_tts_backend_for_engine
+
     # Get all samples for profile
     samples = db.query(DBProfileSample).filter_by(profile_id=profile_id).all()
 
     if not samples:
         raise ValueError(f"No samples found for profile {profile_id}")
 
-    tts_model = get_tts_model()
+    tts_model = get_tts_backend_for_engine(engine)
 
     if len(samples) == 1:
         # Single sample - use directly

backend/requirements.txt

@@ -9,11 +9,18 @@ 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
+
 # Audio processing
 librosa>=0.10.0
 soundfile>=0.12.0

justfile

@@ -0,0 +1,189 @@
+# 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.$PY_MINOR detected. ML packages may not be compatible."
+            echo "Recommended: brew install [email protected]"
+        fi
+        {{ system_python }} -m venv {{ venv }}
+    fi
+    echo "Installing Python dependencies..."
+    {{ pip }} install --upgrade pip -q
+    {{ pip }} install -r {{ backend_dir }}/requirements.txt
+    # Apple Silicon: install MLX backend
+    if [ "$(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

scripts/setup-dev-sidecar.js

@@ -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,
+      0x4d,
-      0xB8, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+      0x5a,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+      0x90,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00,
+      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,
+      0x0e,
-      0x69, 0x73, 0x20, 0x70, 0x72, 0x6F, 0x67, 0x72, 0x61, 0x6D, 0x20, 0x63, 0x61, 0x6E, 0x6E, 0x6F,
+      0x1f,
-      0x74, 0x20, 0x62, 0x65, 0x20, 0x72, 0x75, 0x6E, 0x20, 0x69, 0x6E, 0x20, 0x44, 0x4F, 0x53, 0x20,
+      0xba,
-      0x6D, 0x6F, 0x64, 0x65, 0x2E, 0x0D, 0x0D, 0x0A, 0x24, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+      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
+      0x64,
-      0x01, 0x00, // NumberOfSections: 1
+      0x86, // Machine: AMD64
-      0x00, 0x00, 0x00, 0x00, // TimeDateStamp
+      0x01,
-      0x00, 0x00, 0x00, 0x00, // PointerToSymbolTable
+      0x00, // NumberOfSections: 1
-      0x00, 0x00, 0x00, 0x00, // NumberOfSymbols
+      0x00,
-      0xF0, 0x00, // SizeOfOptionalHeader
+      0x00,
-      0x22, 0x00, // Characteristics: EXECUTABLE_IMAGE | LARGE_ADDRESS_AWARE
+      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+
+      0x0b,
-      0x00, 0x00, // Linker version
+      0x02, // Magic: PE32+
-      0x00, 0x00, 0x00, 0x00, // SizeOfCode
+      0x00,
-      0x00, 0x00, 0x00, 0x00, // SizeOfInitializedData
+      0x00, // Linker version
-      0x00, 0x00, 0x00, 0x00, // SizeOfUninitializedData
+      0x00,
-      0x00, 0x10, 0x00, 0x00, // AddressOfEntryPoint
+      0x00,
-      0x00, 0x00, 0x00, 0x00, // BaseOfCode
+      0x00,
-      0x00, 0x00, 0x00, 0x40, 0x01, 0x00, 0x00, 0x00, // ImageBase
+      0x00, // SizeOfCode
-      0x00, 0x10, 0x00, 0x00, // SectionAlignment
+      0x00,
-      0x00, 0x02, 0x00, 0x00, // FileAlignment
+      0x00,
-      0x06, 0x00, 0x00, 0x00, // OS version
+      0x00,
-      0x00, 0x00, 0x00, 0x00, // Image version
+      0x00, // SizeOfInitializedData
-      0x06, 0x00, 0x00, 0x00, // Subsystem version
+      0x00,
-      0x00, 0x00, 0x00, 0x00, // Win32VersionValue
+      0x00,
-      0x00, 0x20, 0x00, 0x00, // SizeOfImage
+      0x00,
-      0x00, 0x02, 0x00, 0x00, // SizeOfHeaders
+      0x00, // SizeOfUninitializedData
-      0x00, 0x00, 0x00, 0x00, // CheckSum
+      0x00,
-      0x03, 0x00, // Subsystem: CONSOLE
+      0x10,
-      0x60, 0x01, // DllCharacteristics
+      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,
-      0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
+      0x10,
-      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+      0x00,
-      0x00, 0x00, 0x00, 0x00, // LoaderFlags
+      0x00,
-      0x10, 0x00, 0x00, 0x00, // NumberOfRvaAndSizes
+      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();