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Containerfile-gpu
@@ -38,8 +38,8 @@ RUN uv lock && uv sync --locked --no-install-project
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# Installing separately from its dependencies allows optimal layer caching
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RUN uv sync --locked
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-# Test PyTorch was installed with default GPU linux backend (CUDA)
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-#RUN uv run python -c "import torch; print(torch.__version__); assert 'cpu' not in torch.__version__;"
+# Test PyTorch was installed with GPU libraries (CUDA)
+RUN uv run python -c "from nvidia import cuda_runtime"
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# Add executables from .venv to system PATH
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ENV PATH="/rag-content/.venv/bin:$PATH"
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