- Auto-install now only installs the matching TensorRT wheels instead of the multi-GB cuda-toolkit package from PyPI. - Use a single pip install -r call per requirements file for faster dependency resolution and better cache reuse. - Add install-success/failure markers to avoid repeating the install on every ComfyUI startup. - Fix pyproject.toml Repository and PublisherId to point to huchukato/ComfyUI-RIFE-TensorRT-Auto. Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
71 lines
2.7 KiB
Bash
Executable File
71 lines
2.7 KiB
Bash
Executable File
#!/bin/bash
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# FALLBACK install script for ComfyUI RIFE TensorRT Auto (Linux/macOS)
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#
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# NOTE: This is a BACKUP script - auto-installation is recommended!
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#
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# PRIMARY METHOD (Recommended):
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# 1. pip install -r requirements.txt
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# 2. Restart ComfyUI
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# 3. Node auto-detects CUDA and installs TensorRT automatically
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#
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# Use this script ONLY if auto-installation fails!
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#
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# The NVIDIA CUDA Toolkit must already be installed on the system.
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# This script installs only the matching TensorRT wheels via pip.
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#
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echo "FALLBACK INSTALLATION - Use only if auto-installation fails!"
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echo "Detecting CUDA version..."
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# Try to detect CUDA version
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CUDA_VERSION=""
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if command -v nvcc &> /dev/null; then
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CUDA_VERSION=$(nvcc --version | grep "release" | awk '{print $6}' | cut -c2-)
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echo "✅ Found CUDA version: $CUDA_VERSION"
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elif [ -n "$CUDA_PATH" ] && [ -f "$CUDA_PATH/bin/nvcc" ]; then
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CUDA_VERSION=$("$CUDA_PATH/bin/nvcc" --version | grep "release" | awk '{print $6}' | cut -c2-)
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echo "✅ Found CUDA version via CUDA_PATH: $CUDA_VERSION"
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elif [ -n "$CUDA_HOME" ] && [ -f "$CUDA_HOME/bin/nvcc" ]; then
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CUDA_VERSION=$("$CUDA_HOME/bin/nvcc" --version | grep "release" | awk '{print $6}' | cut -c2-)
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echo "✅ Found CUDA version via CUDA_HOME: $CUDA_VERSION"
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else
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echo "⚠️ Could not detect CUDA version automatically"
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echo "Please ensure CUDA is installed and nvcc is in your PATH"
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echo "Or set CUDA_PATH or CUDA_HOME environment variables"
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exit 1
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fi
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# Extract major version
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CUDA_MAJOR=$(echo $CUDA_VERSION | cut -d. -f1)
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echo "📦 Installing requirements for CUDA $CUDA_MAJOR..."
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# Install appropriate requirements based on CUDA version
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if [ "$CUDA_MAJOR" = "13" ]; then
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echo "Installing CUDA 13 requirements (RTX 50 series)"
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echo "Installing base dependencies + CUDA 13 TensorRT..."
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python3 -m pip install --prefer-binary -r requirements.txt
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echo "Installing CUDA 13 specific TensorRT packages..."
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python3 -m pip install --prefer-binary -r requirements_cu13.txt
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elif [ "$CUDA_MAJOR" = "12" ]; then
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echo "Installing CUDA 12 requirements (RTX 30/40 series)"
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echo "Installing base dependencies + CUDA 12 TensorRT..."
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python3 -m pip install --prefer-binary -r requirements.txt
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echo "Installing CUDA 12 specific TensorRT packages..."
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python3 -m pip install --prefer-binary -r requirements_cu12.txt
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else
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echo "Unsupported CUDA version: $CUDA_VERSION"
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echo "Supported versions: CUDA 12.x, CUDA 13.x"
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exit 1
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fi
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if [ $? -eq 0 ]; then
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echo "Fallback installation completed!"
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echo "You can now use ComfyUI RIFE TensorRT Auto node"
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echo "In the future, try auto-installation by just installing requirements.txt"
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else
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echo "Installation failed!"
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exit 1
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fi
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