- Modified migration 092 to clarify the purpose of the catalog prompt slots and removed unnecessary seed data, emphasizing that primary focus data is tenant-specific.
- Updated migration 094 to eliminate the full seed process, reflecting the decision to manage catalog prompt slots content through the admin UI or fallback mechanisms.
- Revised documentation to indicate the absence of migration seeds and the reliance on runtime fallbacks for catalog prompt slots, ensuring clarity for future development.
- Added documentation to the `catalog_prompt_slots.py` file to clarify its role as a global admin catalog requiring authentication and admin role, without tenant context.
- Updated the `check_access_layer_hints.py` script to include `catalog_prompt_slots.py` in the list of exempt routers, ensuring proper access control for admin functionalities.
- Introduced a new function `_resolve_entry_slot_values` to streamline the merging of stored slot values with fallbacks, improving code clarity and maintainability.
- Updated `get_catalog_entry_slots` and `resolve_catalog_prompt_variables` functions to utilize the new fallback logic, enhancing the handling of catalog entries.
- Enhanced the `CatalogPromptSlotsEditor` component to display fallback information for slots, improving user experience in managing catalog prompts.
- Incremented version numbers and updated changelog to reflect the new features and improvements.
- Introduced new catalog context handling in planning prompt functions, allowing for improved integration of planning variables.
- Added optional catalog context parameters in various functions to streamline the merging of planning prompt variables.
- Updated frontend components to include CatalogPromptSlotsEditor for managing prompt slots across different catalog types.
- Enhanced API utilities to support fetching and updating catalog prompt slots, improving backend functionality for catalog management.
- Incremented version numbers and updated changelog to reflect the new features and improvements.
- Added new fields for goal query, user notes, max steps, and search query in the AiPromptPreviewBody to support planning prompts.
- Integrated planning prompt handling in the preview_ai_prompt function, allowing for distinct processing of planning and exercise prompts.
- Introduced LLM usage tracking in openrouter_chat_completion and planning_exercise_suggest functions to monitor AI call metrics.
- Updated frontend components to accommodate new input fields for planning prompts, enhancing user experience and functionality.
- Added a new function `_graph_promotion_transition` to determine the necessary exercise visibility changes during graph promotions.
- Updated the `list_visibility_promotion_candidates` endpoint to utilize the new promotion logic, ensuring accurate exercise visibility handling.
- Enhanced the frontend components to prompt users for exercise visibility adjustments based on graph visibility changes, improving user experience.
- Introduced tests for the new promotion logic to ensure correctness and reliability in visibility transitions.
- Introduced functionality to manage governance clubs for superadmins, allowing for better club selection and organization within the Exercise Progression Graph Panel.
- Implemented state management for clubs, including sorting and filtering options, to improve user experience and accessibility.
- Enhanced the useEffect hook to fetch governance clubs dynamically, ensuring up-to-date club information is available for selection.
- Updated the club selection dropdown to categorize clubs into "My Clubs" and "Other Clubs," improving clarity and usability for users.
- Added functionality to select and manage clubs within the Exercise Progression Graph Panel, allowing users to assign clubs to exercises.
- Introduced state management for club selection and manual entry, improving user experience for platform admins.
- Updated visibility handling to ensure proper governance and club association during exercise promotion.
- Enhanced error handling to provide clearer feedback when no club is selected, ensuring users are guided to make necessary selections.
- Updated `PROJECT_STATUS.md` to reflect the implementation of F15 features, including the unified slot review and handling of `findings_stale`.
- Enhanced `PROGRESSION_GRAPH_SLOT_EDITOR_SPEC.md` with detailed descriptions of new functionalities related to the match dialog and path quality assessments.
- Introduced new functions in `exercise_progression_graphs.py` to validate exercise visibility against progression graph settings, ensuring proper governance.
- Improved frontend components to support new governance parameters (visibility and club_id) in exercise creation workflows.
- Updated documentation in `HANDOVER.md` and `PLANNING_KI_ROADMAP.md` to outline the latest developments and validation results for the F15 features.
- Enhanced utility functions for exercise creation to incorporate governance settings, improving the overall user experience in the path builder and editor.
- Updated the key prop in the ProgressionSlotCard component to use a simpler index-based key, enhancing the stability of component rendering during updates.
- This change aims to prevent potential issues with component re-renders and improve overall performance in the ProgressionGraphEditor.
- Added new functions for computing assignment quality scores and counting step assignment statistics, improving the evaluation of steps in path quality assessments.
- Updated existing methods to incorporate the new scoring logic, enhancing the robustness of path evaluations.
- Introduced UI components in the frontend to display detailed quality assessment results, including handling of split dimensions in path evaluations.
- Enhanced tests to cover new functionalities and ensure accuracy in quality scoring and slot management processes.
