Ramnique Singh 72e71e0ab5 feat(x): apply per-task model recommendations at initial selection ... The backend's modelRecommendations entries are now { assistantModel, taskModels? } (rowboatx-backend#18), mirroring models.json v2 vocabulary. When a provider connect/sign-in seeds the assistant (and ONLY then), its per-task recommendations become visible taskModels overrides — each validated against the live list and skipped when equal to the chosen assistant (only differences are written, same principle as the migration). This restores pre-v2 economics for signed-in task models without hidden defaults: fresh Rowboat sign-ins, new devices, and sign-out→sign-in round trips all land with the lite-tier task models the app used to hardcode — server-controlled, updateable without a release. Saved choices are still never touched: no seeding happens when an assistant already exists. - selection logic moves to @x/shared/initial-selection (core re-exports; the renderer connect flow uses the same implementation) - RowboatApiConfig accepts both the legacy flat shape and the nested one (normalizeModelRecommendation), so backend deploy order and rollback are non-events - llm_initial_model_selected gains task_overrides_seeded Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>		2026-07-24 17:41:31 +05:30
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core	feat(x): apply per-task model recommendations at initial selection	2026-07-24 17:41:31 +05:30
shared	feat(x): apply per-task model recommendations at initial selection	2026-07-24 17:41:31 +05:30