Build Executables #25
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| name: Build Executables | |
| on: | |
| push: | |
| tags: | |
| - 'v*' | |
| workflow_dispatch: | |
| inputs: | |
| tag: | |
| description: '要上传资源的 Release 标签（如 v1.2.0），留空则上传到最新 Release' | |
| required: false | |
| default: '' | |
| permissions: | |
| contents: write | |
| jobs: | |
| build: | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| include: | |
| - os: windows-latest | |
| variant: CPU | |
| platform: Windows | |
| pytorch_url: https://download.pytorch.org/whl/cpu | |
| sep: ";" | |
| shell: pwsh | |
| - os: windows-latest | |
| variant: GPU | |
| platform: Windows | |
| pytorch_url: https://download.pytorch.org/whl/cu121 | |
| sep: ";" | |
| shell: pwsh | |
| - os: ubuntu-latest | |
| variant: CPU | |
| platform: Linux | |
| pytorch_url: https://download.pytorch.org/whl/cpu | |
| sep: ":" | |
| shell: bash | |
| - os: ubuntu-latest | |
| variant: GPU | |
| platform: Linux | |
| pytorch_url: https://download.pytorch.org/whl/cu121 | |
| sep: ":" | |
| shell: bash | |
| runs-on: ${{ matrix.os }} | |
| name: Build ${{ matrix.platform }}-${{ matrix.variant }} | |
| steps: | |
| - name: Checkout code | |
| uses: actions/checkout@v4 | |
| - name: Set up Python | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: '3.10' | |
| - name: Install system dependencies (Linux) | |
| if: runner.os == 'Linux' | |
| run: | | |
| sudo apt-get update | |
| sudo apt-get install -y build-essential libsndfile1 ffmpeg portaudio19-dev | |
| - name: Install FFmpeg (Windows) | |
| if: runner.os == 'Windows' | |
| run: choco install ffmpeg -y | |
| - name: Install Python dependencies | |
| run: | | |
| python -m pip install --upgrade "pip<24.1" | |
| pip install pyinstaller | |
| pip install torch torchaudio --index-url ${{ matrix.pytorch_url }} | |
| pip install omegaconf==2.0.6 --no-deps | |
| pip install PyYAML antlr4-python3-runtime hydra-core | |
| pip install fairseq==0.12.2 --no-deps | |
| pip install "jinja2<3.1.5" | |
| pip install gradio==3.50.2 librosa soundfile scipy numpy praat-parselmouth pyworld faiss-cpu tqdm requests python-dotenv colorama huggingface_hub pedalboard ffmpeg-python av imageio-ffmpeg | |
| pip install demucs torchcrepe --no-deps | |
| pip install julius dora-search lameenc openunmix treetable | |
| python -c "import torch; print(f'PyTorch: {torch.__version__}, CUDA: {torch.cuda.is_available()}')" | |
| - name: Install audio-separator | |
| run: pip install audio-separator onnxruntime | |
| - name: Bundle FFmpeg runtime | |
| shell: bash | |
| run: | | |
| python - <<'PY' | |
| import os | |
| import shutil | |
| import stat | |
| from pathlib import Path | |
| import imageio_ffmpeg | |
| bundle_dir = Path("tools/ffmpeg/bin") | |
| bundle_dir.mkdir(parents=True, exist_ok=True) | |
| ffmpeg_src = Path(imageio_ffmpeg.get_ffmpeg_exe()) | |
| ffmpeg_name = "ffmpeg.exe" if os.name == "nt" else "ffmpeg" | |
| ffmpeg_dest = bundle_dir / ffmpeg_name | |
| shutil.copy2(ffmpeg_src, ffmpeg_dest) | |
| ffmpeg_dest.chmod(ffmpeg_dest.stat().st_mode | stat.S_IXUSR | stat.S_IXGRP | stat.S_IXOTH) | |
| print(f"Bundled ffmpeg: {ffmpeg_dest}") | |
| ffprobe_src = shutil.which("ffprobe") | |
| if ffprobe_src: | |
| ffprobe_name = "ffprobe.exe" if os.name == "nt" else "ffprobe" | |
| ffprobe_dest = bundle_dir / ffprobe_name | |
| shutil.copy2(ffprobe_src, ffprobe_dest) | |
| ffprobe_dest.chmod(ffprobe_dest.stat().st_mode | stat.S_IXUSR | stat.S_IXGRP | stat.S_IXOTH) | |
| print(f"Bundled ffprobe: {ffprobe_dest}") | |
| PY | |
| - name: Download all AI models | |
| shell: bash | |
| env: | |
| PYTHONIOENCODING: utf-8 | |
| run: | | |
| echo "=== Download all base models (HuBERT, RMVPE, UVR5, DeEcho, pretrained) ===" | |
| python tools/download_models.py --all | |
| echo "=== Download Roformer separator models ===" | |
| python -c " | |
| from audio_separator.separator import Separator | |
| import os | |
| model_dir = os.path.join('assets', 'separator_models') | |
| os.makedirs(model_dir, exist_ok=True) | |
| # Vocal separation model | |
| sep = Separator(output_dir='.', model_file_dir=model_dir) | |
| sep.load_model('vocals_mel_band_roformer.ckpt') | |
| del sep | |
| # Karaoke model | |
| sep2 = Separator(output_dir='.', model_file_dir=model_dir) | |
| sep2.load_model('mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956.ckpt') | |
| del sep2 | |
| print('Roformer models downloaded.') | |
| " | |
| echo "=== Verify downloaded models ===" | |
| find assets/ -name "*.pt" -o -name "*.pth" -o -name "*.ckpt" -o -name "*.onnx" | while read f; do | |
| SIZE=$(stat -c%s "$f" 2>/dev/null || stat -f%z "$f") | |
| echo " $f ($(( SIZE / 1048576 )) MB)" | |
| done | |
| - name: Build executable | |
| shell: bash | |
| run: | | |
| SEP="${{ matrix.sep }}" | |
| NAME="AI-RVC-${{ matrix.platform }}-${{ matrix.variant }}" | |
| pyinstaller --name "${NAME}" \ | |
| --onedir \ | |
| --add-data "ui${SEP}ui" \ | |
| --add-data "infer${SEP}infer" \ | |
| --add-data "lib${SEP}lib" \ | |
| --add-data "models${SEP}models" \ | |
| --add-data "tools${SEP}tools" \ | |
| --add-data "i18n${SEP}i18n" \ | |
| --add-data "configs${SEP}configs" \ | |
| --add-data "assets/hubert${SEP}assets/hubert" \ | |
| --add-data "assets/rmvpe${SEP}assets/rmvpe" \ | |
| --add-data "assets/uvr5_weights${SEP}assets/uvr5_weights" \ | |
| --add-data "assets/pretrained_v2${SEP}assets/pretrained_v2" \ | |
| --add-data "assets/separator_models${SEP}assets/separator_models" \ | |
| --hidden-import=torch \ | |
| --hidden-import=torchaudio \ | |
| --hidden-import=gradio \ | |
| --hidden-import=librosa \ | |
| --hidden-import=soundfile \ | |
| --hidden-import=fairseq \ | |
| --hidden-import=audio_separator \ | |
| --hidden-import=demucs \ | |
| --hidden-import=pedalboard \ | |
| --collect-all torch \ | |
| --collect-all torchaudio \ | |
| --collect-all gradio \ | |
| --collect-all gradio_client \ | |
| run.py | |
| - name: Create portable package | |
| shell: bash | |
| run: | | |
| NAME="AI-RVC-${{ matrix.platform }}-${{ matrix.variant }}" | |
| PKG="${NAME}-Portable" | |
| mkdir -p "${PKG}" | |
| # onedir 输出在 dist/NAME/ 目录下，复制全部内容 | |
| cp -r dist/${NAME}/* "${PKG}/" | |
| cp README.md "${PKG}/" | |
| [ -f LICENSE ] && cp LICENSE "${PKG}/" | |
| if [ "${{ matrix.variant }}" = "GPU" ]; then | |
| VARIANT_NOTE="GPU 版（CUDA 12.1），支持 NVIDIA 显卡加速 | |
| 如果没有 NVIDIA 显卡，程序会自动回退到 CPU 推理" | |
| else | |
| VARIANT_NOTE="CPU 版，无需显卡即可运行 | |
| 如需 GPU 加速，请下载 GPU 版本或使用本地安装方式：python install.py" | |
| fi | |
| if [ "${{ matrix.platform }}" = "Windows" ]; then | |
| EXE_NAME="${NAME}.exe" | |
| cat > "${PKG}/使用说明.txt" << HEREDOC | |
| AI-RVC ${{ matrix.platform }} 便携版（${{ matrix.variant }}） | |
| 使用方法： | |
| 双击 ${EXE_NAME} 启动 | |
| 浏览器访问 http://127.0.0.1:7860 | |
| ${VARIANT_NOTE} | |
| AI 模型已内置，无需额外下载 | |
| 无需安装 Python，解压即用 | |
| HEREDOC | |
| else | |
| EXE_NAME="${NAME}" | |
| chmod +x "${PKG}/${EXE_NAME}" | |
| cat > "${PKG}/使用说明.txt" << HEREDOC | |
| AI-RVC ${{ matrix.platform }} 便携版（${{ matrix.variant }}） | |
| 使用方法： | |
| chmod +x ${EXE_NAME} | |
| ./${EXE_NAME} | |
| 浏览器访问 http://127.0.0.1:7860 | |
| ${VARIANT_NOTE} | |
| AI 模型已内置，无需额外下载 | |
| 无需安装 Python，解压即用 | |
| HEREDOC | |
| fi | |
| - name: Compress package | |
| shell: bash | |
| run: | | |
| NAME="AI-RVC-${{ matrix.platform }}-${{ matrix.variant }}" | |
| PKG="${NAME}-Portable" | |
| if [ "${{ matrix.platform }}" = "Windows" ]; then | |
| # 先压缩成 zip | |
| 7z a -tzip "${PKG}.zip" "${PKG}" | |
| # 超过 1.9GB 时删除 zip 改用 7z（压缩率更高） | |
| FILE_SIZE=$(stat -c%s "${PKG}.zip" 2>/dev/null || wc -c < "${PKG}.zip" | tr -d ' ') | |
| if [ "$FILE_SIZE" -gt 1900000000 ]; then | |
| rm "${PKG}.zip" | |
| # 先尝试不分卷的 7z | |
| 7z a "${PKG}.7z" "${PKG}" | |
| SEVENZ_SIZE=$(stat -c%s "${PKG}.7z" 2>/dev/null || wc -c < "${PKG}.7z" | tr -d ' ') | |
| if [ "$SEVENZ_SIZE" -gt 1900000000 ]; then | |
| # 7z 也超限，改用分卷 | |
| rm "${PKG}.7z" | |
| 7z a -v1900m "${PKG}.7z" "${PKG}" | |
| fi | |
| fi | |
| else | |
| tar -czf "${PKG}.tar.gz" "${PKG}" | |
| # 超过 1.9GB 时拆分 | |
| FILE_SIZE=$(stat -c%s "${PKG}.tar.gz" 2>/dev/null || stat -f%z "${PKG}.tar.gz") | |
| if [ "$FILE_SIZE" -gt 1900000000 ]; then | |
| split -b 1900M "${PKG}.tar.gz" "${PKG}.tar.gz.part" | |
| rm "${PKG}.tar.gz" | |
| fi | |
| fi | |
| - name: Upload artifact | |
| uses: actions/upload-artifact@v4 | |
| with: | |
| name: AI-RVC-${{ matrix.platform }}-${{ matrix.variant }} | |
| path: AI-RVC-${{ matrix.platform }}-${{ matrix.variant }}-Portable* | |
| upload-release: | |
| needs: [build] | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: Download all artifacts | |
| uses: actions/download-artifact@v4 | |
| with: | |
| merge-multiple: true | |
| - name: List artifacts | |
| run: ls -lh AI-RVC-* | |
| - name: Determine target tag | |
| id: tag | |
| run: | | |
| if [ "${{ github.event_name }}" = "push" ]; then | |
| echo "tag=${GITHUB_REF#refs/tags/}" >> $GITHUB_OUTPUT | |
| elif [ -n "${{ github.event.inputs.tag }}" ]; then | |
| echo "tag=${{ github.event.inputs.tag }}" >> $GITHUB_OUTPUT | |
| else | |
| LATEST=$(gh release list --repo ${{ github.repository }} --limit 1 --json tagName -q '.[0].tagName') | |
| echo "tag=${LATEST}" >> $GITHUB_OUTPUT | |
| fi | |
| env: | |
| GH_TOKEN: ${{ secrets.GITHUB_TOKEN }} | |
| - name: Upload assets to release | |
| run: | | |
| TAG="${{ steps.tag.outputs.tag }}" | |
| echo "上传资源到 Release: ${TAG}" | |
| # 收集所有构建产物（含分卷文件） | |
| mapfile -t FILES < <(find . -maxdepth 1 -name "AI-RVC-*-Portable*" -type f | sort) | |
| upload_asset_with_retry() { | |
| local tag="$1" | |
| local file="$2" | |
| local attempt | |
| local exit_code | |
| for attempt in 1 2 3; do | |
| echo "上传(${attempt}/3): ${file}" | |
| if timeout 30m gh release upload "${tag}" "${file}" \ | |
| --repo ${{ github.repository }} \ | |
| --clobber; then | |
| return 0 | |
| fi | |
| exit_code=$? | |
| echo "上传失败(退出码=${exit_code}): ${file}" | |
| if [ "${attempt}" -lt 3 ]; then | |
| sleep $(( attempt * 20 )) | |
| fi | |
| done | |
| echo "上传最终失败: ${file}" | |
| return 1 | |
| } | |
| echo "找到以下文件：" | |
| for f in "${FILES[@]}"; do | |
| SIZE=$(stat -c%s "$f" 2>/dev/null || stat -f%z "$f") | |
| echo " $f ($(( SIZE / 1048576 )) MB)" | |
| done | |
| # 逐个上传 | |
| for f in "${FILES[@]}"; do | |
| upload_asset_with_retry "${TAG}" "$f" | |
| done | |
| echo "全部上传完成" | |
| env: | |
| GH_TOKEN: ${{ secrets.GITHUB_TOKEN }} |