- Introduced `auto_refine_stage_spec` to `ProgressionPathSuggestRequest`, enabling optional refinement of stage specifications during the rematch process.
- Updated `_run_roadmap_rematch_loop` to incorporate stage specification refinements, logging changes for better tracking of adjustments made during rematching.
- Enhanced `suggest_progression_path` to include refine logs in the output, providing clearer insights into the refinement process.
- Added utility functions for formatting refine log entries, improving the display of refinement actions in the frontend components.
- Updated frontend components to display refine logs, enhancing user feedback on stage specification adjustments during progression analysis.
- Bumped version to 0.8.227 to reflect the new features and improvements.
- Added support for displaying optimization hints and rematch logs in the Progression Findings Panel, improving user feedback on potential enhancements.
- Introduced new utility functions for formatting rematch log entries and resolving hint slot indices, enhancing clarity in displayed information.
- Updated the Progression Graph Editor to handle rematch actions and display relevant match summaries, ensuring comprehensive insights during progression analysis.
- Enhanced the utility functions to support the new features, ensuring robust handling of optimization actions and rematch logic.
- Updated `suggest_progression_path` to ensure unique gap fill offers are collected and added based on their IDs, improving the relevance of suggestions.
- Refined the logic for setting `slot_status` and handling `gap_offer` and `proposal_key` in steps, enhancing clarity in progression path management.
- Improved the `collectGapOffersFromApiResponse` function to consolidate gap offers from various sources, ensuring comprehensive offer retrieval.
- Enhanced the handling of unfilled slots in `applyMatchStepsToSlots`, ensuring proper assignment of proposals and gap offers.
- Added tests to validate the new logic for gap fill offers and slot assignments, ensuring robustness in path suggestion features.
- Added `_safe_tsquery_fragment` to sanitize learning goal input for SQL queries, improving query safety.
- Introduced `_fetch_learning_goal_library_candidate_ids` to retrieve exercise IDs matching learning goals, enhancing exercise relevance in roadmap suggestions.
- Enhanced `_match_roadmap_slot` to utilize learning goal candidates, improving the accuracy of supplemental exercise selection.
- Implemented `_pick_roadmap_rank_fallback` to provide a fallback mechanism for selecting the best exercise when strict matching fails, ensuring better exercise retrieval.
- Updated tests to validate the new learning goal retrieval and fallback logic, ensuring robustness in exercise selection processes.
- Introduced new functions for handling exercise visibility and retrieval based on progression graph context, including `fetch_exercise_rows_by_ids_for_graph`.
- Updated `_load_supplemental_exercise_rows` to incorporate graph visibility rules, improving the accuracy of exercise retrieval.
- Enhanced `_run_path_step_retrieval` to utilize preloaded supplemental exercise rows, optimizing performance and clarity in path step processing.
- Added `exercise_title_equivalent_to_stage_goal` function to improve title matching against learning goals, enhancing exercise relevance.
- Updated tests to validate new retrieval logic and title equivalence functionality, ensuring robustness in exercise selection processes.
- Added `preserve_slot_assignments` and `retrieval_boost_exercise_ids` to `ProgressionPathSuggestRequest` for improved handling of exercise suggestions.
- Refactored `_supplemental_exercise_ids_from_body` to incorporate retrieval boost exercise IDs, ensuring they are prioritized over slot assignments.
- Updated `_build_steps_roadmap_first` to conditionally preserve slot assignments based on the new flag.
- Enhanced tests to validate the new retrieval boost logic and its integration with existing slot assignment handling.
- Introduced `slot_assignments` to `ProgressionPathSuggestRequest` for improved handling of existing slot assignments in path building.
- Implemented `_slot_assignments_by_major_index` and `_path_step_from_slot_assignment` functions to facilitate the integration of slot assignments into the path generation process.
- Updated `_build_steps_roadmap_first` to utilize slot assignments, enhancing the accuracy of path steps based on existing exercise slots.
- Enhanced `detect_path_gaps` to skip empty slots, preventing unnecessary errors during gap detection.
- Added tests to validate the new slot assignment handling and ensure robustness in path generation logic.
- Added `tzdata` installation in the Dockerfile to support time zone handling in Linux environments.
- Increased `PIP_DEFAULT_TIMEOUT` and added retry logic for pip installations to enhance reliability during dependency installation.
- Updated `requirements.txt` to conditionally include `tzdata` for Windows platforms, ensuring compatibility across different operating systems.
- Updated `suggest_progression_path` to include AI-generated gap fill offers when exercises are missing, improving the relevance of suggested paths.
- Introduced a match summary to provide insights on library matches and gap fill offers, enhancing user feedback in the `ProgressionGraphEditor`.
- Refined the `pick_best_path_hit` function to ensure proper handling of roadmap stage matches based on primary topics.
- Added tests to validate the new gap fill offer logic and match summary functionality, ensuring robustness in path suggestion features.
- Introduced `resolve_path_primary_topic` function to enhance the determination of primary topics from goal queries and semantic briefs, improving exercise relevance.
- Updated `_match_roadmap_slot` and `detect_off_topic_steps` functions to utilize the new primary topic resolution logic, ensuring accurate topic identification.
- Enhanced tests to validate the functionality of primary topic resolution and its impact on exercise selection and off-topic detection.
- Improved handling of primary topics in the `ExerciseProgressionPathBuilder` and related components for better integration with the overall path-building process.
- Improved off-topic step handling by incorporating roadmap major step indices for better indexing and detection.
- Refactored `collect_gap_fill_specs` to streamline the insertion logic for off-topic steps, ensuring correct placement based on major step indices.
- Introduced `_normalize_roadmap_steps_coverage` function to standardize roadmap steps coverage, enhancing the handling of missing slots.
- Added `prune_stripped_after_rematch` function to clean up stripped off-topic steps after rematching, improving the overall rematching process.
- Updated tests to validate new rematching and off-topic handling features, ensuring robustness against edge cases.
- Incremented application version to reflect these updates.
- Refactored `ExerciseProgressionGraphPanel` to support a create dialog for new progression graphs, improving user experience.
- Integrated `ProgressionGraphListCard` for better visualization of existing graphs and streamlined management.
- Updated `ProgressionGraphEditor` to handle start/target analysis and improved draft hydration with AI suggestions.
- Added utility functions for managing structured responses from AI, enhancing the planning process.
- Incremented application version to reflect these updates.
- Implemented functions to resolve neighboring steps based on major indices and build AI context for unfilled roadmap stages.
- Enhanced `try_suggest_ai_stage_step` to generate AI proposals for empty roadmap stages, improving user experience in gap filling.
- Updated `build_gap_fill_offer` to utilize major step neighbors for better context in offers related to unfilled slots.
- Added tests to ensure correct functionality of AI suggestion handling in the context of roadmap gaps.
- Incremented application version to reflect these updates.
- Implemented `_build_evaluate_empty_slot_gap_specs` function to generate gap offer specifications for unfilled roadmap slots in evaluate-only mode.
- Enhanced `ProgressionFindingsPanel` to display AI offers for empty slots and gaps, improving user interaction and clarity.
- Updated `ProgressionGraphEditor` and `ProgressionSlotCard` components to support new functionalities for managing slots and offers.
- Refactored utility functions in `progressionGraphDraft.js` to streamline slot management and offer handling.
- Incremented application version to reflect these updates.
- Introduced EvaluateStepPayload class to facilitate evaluation of exercise steps with optional attributes for AI proposals and roadmap details.
- Added SlotContentEntry and SlotExerciseContent classes to manage exercise content within the progression graph planning artifact.
- Updated GraphPlanningRoadmapArtifact to include new slot contents and last findings attributes for improved data handling.
- Enhanced Exercise Progression Graph Panel with links to the new Slot Editor for streamlined editing of progression graphs.
- Incremented application version to reflect these updates.
