- Implemented a maximum of 3 exercises per preview request to prevent Gateway-504 errors, improving the stability of the exercise enrichment process.
- Adjusted batch sizes for applying exercises and previewing to optimize performance and resource management.
- Updated the frontend to reflect changes in preview handling, including user notifications about chunk sizes and potential timeouts.
- Incremented version to 0.8.180 and updated changelog to document these enhancements and fixes.
- Introduced the `exercise_enrichment_admin` API for batch exercise enrichment, allowing superadmins to filter candidates, preview, and apply skills.
- Updated the access layer documentation to include the new endpoint and its exempt status.
- Enhanced the frontend with a new admin page for exercise enrichment and updated navigation to include this feature.
- Incremented version to 0.8.179 and updated changelog to reflect these additions and improvements.
- Updated the planning exercise retrieval process to implement a multistage approach, ranking the entire visible library deterministically against the expectation profile.
- Removed the previous profile OR pool mechanism, simplifying the retrieval logic and ensuring full-text search is only used as a scoring signal.
- Adjusted the `compose_retrieval_phase` function to accommodate the new full library ranking strategy.
- Incremented version to 0.8.177 and updated changelog to reflect these changes in planning exercise capabilities.
- Introduced the ExerciseAiQuickCreateTeaser component for a compact entry point in the exercise creation process.
- Updated ExercisePickerModal to integrate the new teaser, allowing users to expand and create exercises directly from the search results.
- Enhanced the quick create functionality with dynamic headlines and hints based on user input and context.
- Refactored conditional rendering logic to improve user experience when no exercises are found.
- Added support for the new planning exercise expectation profile slug in the AI prompt runtime.
- Refactored SQL parameter handling in the planning exercise retrieval process to ensure correct binding for full-text search.
- Updated the planning exercise suggestion logic to incorporate LLM expectation handling, improving the accuracy of exercise recommendations.
- Introduced new functions to determine when to run the LLM expectation pipeline, enhancing the decision-making process for exercise suggestions.
- Incremented version to 0.8.176 and updated changelog to reflect these enhancements in planning AI capabilities.
- Introduced new functions to generate skill profiles from exercise IDs, improving the ability to summarize skills for both units and sections.
- Updated the planning target profile to incorporate section-specific exercise IDs, allowing for more granular skill tracking and context.
- Enhanced the ExercisePickerModal and related pages to support section context, including titles, guidance notes, and exercise counts.
- Implemented expectation mode handling in the planning target pipeline to differentiate between planning references and query-only scenarios.
- Incremented version to 0.8.174 and updated changelog to reflect these enhancements in planning AI capabilities.
- Replaced the previous exercise matching logic with a new multistage planning retrieval process, improving the accuracy of exercise suggestions.
- Introduced LLM gates to limit LLM calls based on query length and intent application, optimizing performance and resource usage.
- Updated the `compose_retrieval_phase` function to include profile preselection, enhancing the retrieval process.
- Incremented version to 0.5.0 and updated changelog to reflect these significant enhancements in planning AI capabilities.
- Introduced a constant `PLANNING_SUGGEST_LIMIT` set to 50 to align with backend constraints for exercise suggestions.
- Updated the API request limit in `ExercisePickerModal` to utilize the new constant, ensuring compliance with backend specifications.
- Made `unit_id` and `group_id` optional in `PlanningExerciseSuggestRequest` to support client context without a saved unit.
- Refactored `_load_group_recent_exercise_ids` to handle cases where `exclude_unit_id` is optional.
- Introduced `build_client_planning_context_pack` for improved context handling in client-free searches.
- Updated `suggest_planning_exercises` to utilize the new client context pack when `unit_id` is not provided.
- Incremented version to 0.8.172 and updated changelog to reflect these enhancements in the planning AI capabilities.
- Introduced `planningUnitId` and `expectPlanningSearch` props to better manage planning context for exercise suggestions.
- Refactored logic to resolve planning unit ID and construct active planning context, enhancing the accuracy of exercise suggestions.
- Implemented checks to block planning search when necessary, providing clearer user feedback in the UI.
- Updated `TrainingUnitEditPage` to pass the correct planning unit ID, ensuring seamless integration with the exercise picker.
- Updated `effectivePickerQuery` logic to improve search handling based on planning context, allowing for a single input field in planning mode.
- Simplified query construction by utilizing `effectivePickerQuery` throughout the component, enhancing clarity and user experience.
- Adjusted UI elements and labels to better reflect the context of the search, providing clearer guidance for users.
- Modified `TrainingUnitEditPage` to ensure proper unit ID resolution, improving integration with the exercise picker.
- Introduced `effectivePickerQuery` to streamline search input handling, combining `debouncedSearch` and `debouncedAi` for improved query accuracy.
- Updated the `useExerciseAiQuickCreateFields` hook to use the new effective query, enhancing the quick create functionality.
- Modified conditional checks to utilize `effectivePickerQuery`, ensuring better user feedback based on search input.
- Improved placeholder text and labels for clarity in the search fields, enhancing user experience during exercise selection.
- Introduced the Scenario Pipeline for planning exercises, allowing for more nuanced query handling and exercise suggestions based on user intent.
- Enhanced the `suggestPlanningExercises` API to include `include_llm_intent`, `scenario_kind`, and `query_intent_summary`, improving the context provided to the frontend.
- Updated the `ExercisePickerModal` to display new information related to query intent and scenario classification, enhancing user experience during exercise selection.
- Incremented application version to 0.8.171 and updated changelog to document the new features and improvements in the planning AI capabilities.
- 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.
- Implemented Phase 1.1 of the planning exercise suggestion functionality, integrating `ExerciseMatchProfile` and `PlanningTargetProfile` for improved exercise scoring based on profile dimensions.
- Updated the `suggestPlanningExercises` API to include a new `retrieval_phase` and `target_profile_summary`, enhancing the context provided to the frontend.
- Enhanced the `ExercisePickerModal` to display additional information from the planning target profile, including focus areas and top skills, improving user experience during exercise selection.
- Incremented application version to 0.8.169 and updated changelog to reflect 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.
