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Practical, Linux-first guide to packaging AI apps without source-build pain: prep dev tools, use isolated venvs, prefer platform-matched binary wheels (manylinux/musllinux, CUDA/ROCm), lock deps with pip-compile and hashes, package via pyproject.toml wheels with optional GPU extras, keep installs lean and secure, avoid pitfalls (sudo pip, CUDA mismatches), and ship with apt/dnf/zypper, pipx, twine, and TestPyPI-ready steps.