Enhance MLX and PyTorch Backend Integration

- Added support for MLX backend on Apple Silicon, enabling optimized performance for TTS and STT tasks.
- Implemented platform detection to dynamically select between MLX and PyTorch based on the runtime environment.
- Updated build process to include MLX-specific dependencies and configurations for macOS.
- Refactored backend code to improve model loading and inference logic, accommodating backend-specific requirements.
- Enhanced documentation to clarify backend selection and performance benefits for different platforms.
- Streamlined installation instructions and troubleshooting guidance for MLX-related issues.

tauri/src-tauri/src/main.rs

@@ -635,13 +635,6 @@ pub fn run() {
                 }
             }
 
-            // Get all windows and open devtools on the first one
-            if let Some((_, window)) = app.webview_windows().iter().next() {
-                window.open_devtools();
-                println!("Dev tools opened");
-            } else {
-                println!("No window found to open dev tools");
-            }
             Ok(())
         })
         .invoke_handler(tauri::generate_handler![