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ADDED MLX FOR SUPER FAST GENERATIONS ON APPLE SILICON
- Added support for MLX backend on Apple Silicon, enabling optimized performance for TTS and STT tasks. - Updated release workflow to include MLX-specific dependencies and configurations for macOS platforms. - Refactored backend code to dynamically select between MLX and PyTorch based on the runtime environment. - Enhanced model loading and inference logic to accommodate backend-specific requirements, including updated model IDs and hidden imports. - Improved health check and model status reporting to reflect the active backend type. - Streamlined caching mechanisms to support both backend types, ensuring compatibility and performance.
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@@ -17,15 +17,19 @@ jobs:
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- platform: 'macos-latest'
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args: '--target aarch64-apple-darwin'
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python-version: '3.12'
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backend: 'mlx'
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- platform: 'macos-15-intel'
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args: '--target x86_64-apple-darwin'
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python-version: '3.12'
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backend: 'pytorch'
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# - platform: 'ubuntu-22.04'
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# args: ''
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# python-version: '3.12'
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# backend: 'pytorch'
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- platform: 'windows-latest'
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args: ''
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python-version: '3.12'
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backend: 'pytorch'
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runs-on: ${{ matrix.platform }}
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@@ -57,6 +61,11 @@ jobs:
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pip install pyinstaller
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pip install -r backend/requirements.txt
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- name: Install MLX dependencies (Apple Silicon only)
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if: matrix.backend == 'mlx'
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run: |
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pip install -r backend/requirements-mlx.txt
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- name: Build Python server (Linux/macOS)
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if: matrix.platform != 'windows-latest'
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run: |
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@@ -133,7 +142,8 @@ jobs:
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See the assets below to download and install this version.
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### Installation
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- **macOS**: Download the `.dmg` file
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- **macOS (Apple Silicon)**: Download the `aarch64.dmg` file - uses MLX for fast native inference
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- **macOS (Intel)**: Download the `x64.dmg` file - uses PyTorch
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- **Windows**: Download the `.msi` installer
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- **Linux**: Download the `.AppImage` or `.deb` package
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