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.

backend/platform_detect.py

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