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# we always want composite metric definitions to be updated - should_update = content_id.startswith("composite_metric_def:") - - # if we are updating a metric or test description, we check if the text - # has changed from the last time it was logged, and only update if it has - if content_id.split(":", 1)[0] in ["metric_description", "test_description"]: - try: - md = await api_client.aget_metadata(content_id) - # if there is an existing description, only update it if the new one - # is different and is an AI-generated description - should_update = ( - md["text"] != text if revision_name == AI_REVISION_NAME else False - ) - logger.debug(f"Check if description has changed: {should_update}") - except Exception: - # if exception, assume its not created yet TODO: don't catch all - should_update = True - - if should_update: - if revision_name: - content_id = f"{content_id}::{revision_name}" + if revision_name: + content_id = f"{content_id}::{revision_name}" - logger.debug(f"Updating metadata for `{content_id}`") + logger.debug(f"Updating metadata for `{content_id}`") - await api_client.alog_metadata(content_id, text, _json) + await api_client.alog_metadata(content_id, text, _json) def check_for_sensitive_data(data: pd.DataFrame, inputs: List[VMInput]):