feat(WIP): implement llm for metadata conversion #3
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kellytea
commented
Sep 30, 2025
kellytea
commented
- working on conversion between known formats
- using litellm
- still need to validate content of the llm response + refactor llm runner configuration
- working on conversion between known formats -using litellm
sgfost
reviewed
Oct 1, 2025
| "Convert the SOURCE_DATA to match TARGET_MODEL_SCHEMA.\n" | ||
| "SOURCE_DATA:\n" + json.dumps(source_dict) + "\n\n" | ||
| "SOURCE_MODEL_SCHEMA:\n" + json.dumps(source_model.schema()) + "\n\n" | ||
| "TARGET_MODEL_SCHEMA:\n" + json.dumps(target_model.schema()) + "\n\n" |
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I bet context/docs (definitions of terms, etc.) for the schemas might help with results
we could put a description for all the fields in the pydantic models so that it would end up in the jsonschema from schema(), but this may be a lot of work, even with an initial pass of having AI fill them out from the docs below
alternatively, just throw in the full text of the documentation
https://codemeta.github.io/terms/
https://datacite-metadata-schema.readthedocs.io/en/4.6/
https://github.com/citation-file-format/citation-file-format/blob/main/schema-guide.md
sgfost
reviewed
Oct 1, 2025
sgfost
reviewed
Oct 1, 2025
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