python_lib
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Tips and guidelines specific to the development of the Streamlit Python library, not applicable to scripts and e2e tests.
52 tagged deep learning, measured the same way as everything else here.
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Tips and guidelines specific to the development of the Streamlit Python library, not applicable to scripts and e2e tests.
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This directory contains product and tech specs for Streamlit features.
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Changes to these high-fan-out internals can affect every message, delta, element, or rerun. Keep work in them minimal, and benchmark changes with representative stress-test apps.
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New model classes should start in physicsnemo/experimental/nn or physicsnemo/experimental/models during development, where backward compatibility is not guaranteed.
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All forward and public methods must validate tensor shapes at the beginning, wrapped in torch.compiler.iscompiling() guard, with standardized error messages.
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Use checkminversion() to check optional dependencies without importing, and @requireversion decorator to protect version-specific features; pyproject.toml is the single source of truth for dependencies.
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Python code style — imports, third-party submodules, and docstrings.
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Tests and coverage when changing src/, scripts/, or tests/.
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Visible console, TensorBoard with train jobs, logs/tmp captures, no repo-root tmp.
ssdeanx/secure-rag-multi-agent
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Apply the general coding guidelines to all code.
ssdeanx/secure-rag-multi-agent
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The Memory Bank is a hierarchical documentation system designed to survive AI memory resets. It organizes project knowledge into: project brief → context files → designs → requirements → tasks → progress. Every task must begin with reading ALL memory bank files. Use spec-driven development with EARS format…