- Added support for club feature quota bypass based on portal roles and profile grants in the capabilities check.
- Introduced new functions to handle quota bypass logic in club feature access and consumption.
- Updated the FeatureUsageBadge component to reflect platform exemptions for features.
- Incremented application version to 0.8.195 and database schema version to 20260606083 to reflect these changes.
- Enhanced backend routers to include new logic for consuming club features during AI-related actions.
- Introduced `email_verified` and `account_state` attributes in the `TenantContext` to improve user state management.
- Updated the `resolve_tenant_context` function to dynamically fetch `email_verified` status from the database and determine `account_state` based on user roles and memberships.
- Implemented `assert_min_account_state` checks across various endpoints to enforce access control based on user account status.
- Incremented version to 1.1.0 in version.py to reflect these enhancements in tenant context management and access control.
- Introduced `probe_club_feature_access` to check club feature limits and log access attempts without blocking by default.
- Added `_live_inventory_count` function to retrieve current counts for specific features, enhancing feature limit management.
- Updated various endpoints to utilize the new probing functionality, ensuring compliance with club feature access rules.
- Incremented version to 1.1.0 in version.py to reflect these enhancements in club feature management.
- Incremented version to 0.8.185, reflecting the implementation of Phase C3 features.
- Introduced the `POST /api/planning/progression-path-suggest` endpoint for generating exercise progression paths.
- Enhanced the ExerciseProgressionGraphPanel with a new ExerciseProgressionPathBuilder for reviewing and saving paths.
- Updated changelog to document the new capabilities in planning AI functionality.
- Implemented optional LLM-Rerank functionality in the planning exercise suggestion process, allowing for improved exercise ranking based on user-defined criteria.
- Updated the `suggestPlanningExercises` API to accept `planned_exercise_ids` for client-side overrides, enhancing flexibility in exercise selection.
- Enhanced the `ExercisePickerModal` to reflect LLM ranking status and support new planning context features.
- Incremented application version to 0.8.170 and updated changelog to document the new features and improvements in the planning AI capabilities.
- Added new planning AI functionality with the introduction of the `suggestPlanningExercises` API endpoint for context-based exercise suggestions.
- Enhanced `ExercisePickerModal` to utilize planning context, allowing for a more tailored exercise selection experience.
- Updated `TrainingUnitEditPage` to pass planning context to the exercise picker, improving integration with the new planning features.
- Incremented application version to 0.8.167 and updated changelog to reflect the new planning AI capabilities and related enhancements.
