Update remaining converters for the flat (one-model-per-document) Ossie schema

[jbonofre]

Background

#383 moved the Ossie document schema to a single semantic model defined directly at the document root, dropping the semantic_model: [...] list wrapper. Since then, each converter has been fixed one at a time, only after its own CI happened to re-trigger and turn red:

• Fix Microsoft converter for flat documents #407 fixed the Microsoft converter.
• Fix Sigma and NVIDIA GSF converters for flat semantic model documents #417 fixes the Sigma and NVIDIA GSF converters, plus the dbt and wisdom converters (which share the python/ package's OssieDocument model and would have broken the moment it was made to match the schema).

While working on #417, I found the same latent break in the remaining converters — none of them are currently red in CI, because their path-scoped workflows simply haven't re-run since #383 landed, but their fixtures/source still reference the old wrapper shape and will fail the moment something re-triggers their CI (the same way #416's license-header commit accidentally did for Sigma/NVIDIA GSF).

Affected

Confirmed via grep -rn "semantic_model:" over fixtures/source, and via gh run list showing no CI run for any of these since #383 (2026-09-16):

• converters/databricks (fixtures)
• converters/orionbelt (fixtures)
• converters/ontology (fixtures, plus the root examples/flights.yaml it vendors a copy of)
• converters/gooddata (fixtures)
• converters/omni (fixtures)
• converters/honeydew (source + tests)
• converters/snowflake (source)
• converters/salesforce (Java/Maven — source + test resources)
• converters/polaris (Java/Maven — source + test resources)

Suggested approach

Same pattern as #407 and #417: read/write the flat document shape (name/datasets/... at the root, no semantic_model: wrapper, no root-level dialects/vendors), update fixtures, and regenerate any snapshot tests. The Python converters can mostly follow the Sigma/NVIDIA GSF/dbt/wisdom diff in #417 as a template; the Java converters (salesforce, polaris) will need their own look since they don't share that tooling.

🤖 Generated with Claude Code

[eisber]

Thanks for cataloguing these. I mapped the affected list against the open work before starting parallel branches:

• Migrate converters and Python SDK to flat semantic model documents #396 covers all nine converters listed here: Databricks, Orionbelt, Ontology, GoodData, Omni, Honeydew, Snowflake, Salesforce, and Polaris. It also covers Sigma, NVIDIA, dbt, and Wisdom.
• Fix Sigma and NVIDIA GSF converters for flat semantic model documents #417 overlaps Sigma, NVIDIA, dbt, and Wisdom.
• Migrate converters and Python SDK to flat semantic model documents #396 currently has all 50 checks green. Importantly, it also updates the converter workflow path filters so future core-spec/**, example, and shared Python-model changes actually retrigger the dependent suites; Fix Sigma and NVIDIA GSF converters for flat semantic model documents #417 fixes the immediate converters but does not close that trigger gap.

Michael and I recently worked through the same migration for the Power BI converter in #407, including schema validation, installed-CLI round trips, Power BI stash/relationship/measure preservation, and TOM structural checks. We're happy to help review or run focused validation on #396, especially around converter round-trip invariants and the CI trigger changes.

Since the currently listed converter scopes are already covered, I won't start competing per-converter PRs unless maintainers prefer splitting #396. If a split is preferred, point us at a converter and we'll take it through implementation and tests.