huchukatoandDevin
1427bdef9f
- 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>
22 lines
839 B
Plaintext
22 lines
839 B
Plaintext
# Base dependencies - TensorRT will be auto-installed based on CUDA detection
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# The node will automatically detect CUDA 12/13 and install appropriate TensorRT packages.
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# The NVIDIA CUDA Toolkit must already be installed on the system; it is NOT installed via pip.
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#
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# Installation happens automatically when the node loads for the first time
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# No manual TensorRT installation required!
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# Base dependencies that work with any CUDA version
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einops
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colored
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polygraphy
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cuda-python
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requests
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tqdm
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# Note: TensorRT packages are auto-installed on first node load:
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# CUDA 13: tensorrt_cu13==10.15.1.29 (RTX 50 series)
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# CUDA 12: tensorrt-cu12==10.13.3.9 (RTX 30/40 series)
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#
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# Manual installation files are provided for reference only:
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# - requirements_cu12.txt (CUDA 12 specific)
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# - requirements_cu13.txt (CUDA 13 specific) |