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Schematerial translates between heterogeneous materials-science data models by generating semantic crosswalks, executable mappings, and human-in-the-loop alignment reports.

AI agents assist with schema inspection, ontology grounding, ambiguity detection, and evidence-based mapping suggestions.

Local development

Prerequisites: uv and Python >=3.12.

uv sync                  # install deps + editable package into .venv
uv run pytest            # run tests
uv run ruff check .      # lint
uv run pyright           # type check

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a translation layer assistant between heterogeneous data models, where AI agents help infer, explain, validate, and maintain semantic crosswalks

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