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Enhance MLX and PyTorch Backend Integration

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- 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.
This commit is contained in:
Jamie Pine
2026-01-29 23:11:48 -08:00
parent 081f45e680
commit 94487f32a5
17 changed files with 200 additions and 82 deletions
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Makefile
+5
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@@ -48,6 +48,11 @@ 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
@if [ "$$(uname -m)" = "arm64" ] && [ "$$(uname)" = "Darwin" ]; then \
echo -e "$(BLUE)Detected Apple Silicon - installing MLX dependencies...$(NC)"; \
$(PIP) install -r $(BACKEND_DIR)/requirements-mlx.txt; \
echo -e "$(GREEN)✓ MLX backend enabled (native Metal acceleration)$(NC)"; \
fi
$(PIP) install git+https://github.com/QwenLM/Qwen3-TTS.git
@echo -e "$(GREEN)✓ Python environment ready$(NC)"