- Introduced new functions `_off_topic_semantic_scores_by_slot` and `_score_exercise_stage_fit_for_spec` to improve the evaluation of off-topic steps and exercise stage fit, enhancing the quality assessment process.
- Updated `_run_unified_slot_improvement_review` to incorporate off-topic scores and exercise stage fit scoring, refining the decision-making process for slot suggestions.
- Enhanced existing logic to streamline the handling of slot scores and improve the overall robustness of slot management in path evaluations.
- Introduced `_parse_slot_refs_from_text` to extract and convert slot references from text, improving the handling of user input in path evaluations.
- Updated `_problematic_slots_from_path_qa` to utilize the new parsing function, enhancing the identification of problematic slots based on various hints and issues.
- Enhanced `ProgressionGraphEditor` and `ProgressionOptimizeCompareModal` to better display identified problem slots and their associated reasons, improving user feedback during evaluations.
- Added tests for new parsing functionality and its integration with existing slot management processes, ensuring robustness in slot reference handling.
- Introduced `_resolve_hint_major_index` to accurately map hints to major step indices, improving the handling of optimization hints in path evaluations.
- Added `_problematic_slots_from_path_qa` to identify and categorize problematic slots based on baseline QA, enhancing the quality assessment process.
- Updated `_slot_suggestion_accepted` to incorporate new parameters for slot problems and stage specifications, refining the decision-making process for slot suggestions.
- Enhanced `ProgressionGraphEditor` to improve user notifications regarding identified issues and suggestions, ensuring clearer communication of path evaluation results.
- Modified `buildProgressionComparePayload` and `buildUnifiedSlotReviewComparePayload` to support baseline evaluations, streamlining the comparison process for proposed paths.
- Added `_quick_evaluate_steps_qa` function to streamline path quality assessment without recursive API calls, enhancing performance for slot comparisons.
- Introduced `compute_deterministic_path_quality_score` to provide a heuristic quality score based on gaps and off-topic steps, improving evaluation accuracy.
- Updated `_run_unified_slot_improvement_review` to utilize the new quick evaluation method, optimizing the review process and integrating quality scoring.
- Enhanced `build_path_qa_summary` to include quality score calculations, ensuring comprehensive feedback on path evaluations.
- Refactored related functions for improved clarity and efficiency in handling path quality assessments.
- Introduced new fields in `ProgressionPathSuggestRequest` for baseline evaluation and incremental scoring, improving the assessment of proposed paths.
- Implemented `_apply_slot_diff_to_steps` and `_score_incremental_slot_diffs` functions to manage slot differences and evaluate their impact on quality scores.
- Updated `ProgressionGraphEditor` to streamline the match comparison flow, integrating new evaluation parameters and improving user notifications.
- Enhanced `ProgressionOptimizeCompareModal` to better display proposed path suggestions, including pro/con evaluations and quality delta metrics.
- Refactored utility functions for clearer handling of slot differences and improved overall data management in the progression graph editor.
- Introduced new utility functions for comparing slot differences, including `compareDiffKind`, `annotateCompareDiffKinds`, and various filtering functions to streamline the comparison process.
- Updated `ProgressionGraphEditor` to utilize the new comparison logic, improving the handling of slot differences and user notifications.
- Enhanced `ProgressionOptimizeCompareModal` to better manage proposed path suggestions, including clearer messaging and improved selection handling for optional replacements.
- Adjusted frontend components to reflect changes in comparison logic, ensuring a more intuitive user experience in managing progression paths.
- Introduced `buildProgressionComparePayload` to create a structured comparison response from baseline and proposed evaluation results, enhancing clarity in slot differences.
- Refactored `fetchMatchCompare` to `fetchFullMatch` for improved clarity and functionality in fetching progression paths.
- Updated `runMatchCompareFlow` to streamline the evaluation process, integrating baseline and match results for a comprehensive comparison.
- Enhanced utility functions for managing slot differences and gap fill offers, improving overall data handling in the progression graph editor.
- Adjusted frontend components to reflect these changes, ensuring a more intuitive user experience in managing progression paths.
- Removed the `try_suggest_ai_stage_step` function from `_enrich_roadmap_unfilled_gap_offers`, simplifying the gap fill offer generation process.
- Updated `_run_evaluate_only_path_qa` and `suggest_progression_path` to disable AI calls and proposals, enhancing control over evaluation parameters.
- Adjusted `ProgressionGraphEditor` to reflect changes in API requests, ensuring consistent handling of evaluation data.
- Added a new test to validate the behavior of proposed QA when no slot differences are present, improving test coverage for comparison logic.
- Integrated `try_suggest_ai_stage_step` to suggest AI-generated gap fill steps based on user input, improving the automation of the planning process.
- Updated `_enrich_roadmap_unfilled_gap_offers` to conditionally include AI gap fill proposals, enhancing the offer generation logic.
- Implemented `_merge_gap_fill_offers_from_steps` to consolidate gap fill offers from various steps, ensuring a comprehensive list of available offers.
- Modified `ProgressionGraphEditor` to utilize the new merging logic for gap fill offers, improving the user experience in managing offers.
- Enhanced utility functions to streamline the collection and filtering of gap fill offers from API responses.
- Bumped version to reflect the new features and improvements.
- Updated `suggest_progression_path` to utilize `evaluate_steps` for improved validation, ensuring at least one evaluation step is provided.
- Modified frontend components to enhance user experience in the comparison process, including clearer messaging and improved dialog handling.
- Adjusted `ProgressionGraphEditor` to streamline the comparison flow and integrate new evaluation parameters.
- Enhanced `ProgressionOptimizeCompareModal` to reflect changes in comparison logic, allowing for better user interaction with proposed path suggestions.
- Bumped version to reflect the new features and improvements.
- Introduced `_baseline_slot_accepts_rematch_suggestion` to filter out filled or invalid slots from rematch suggestions, improving the accuracy of rematch logic.
- Updated `_build_rematch_suggestion_diffs` to skip non-eligible baseline slots, streamlining the rematch suggestion process.
- Added `_evaluate_steps_for_compare_qa` to evaluate steps against the current state, enhancing the quality assessment during progression path suggestions.
- Modified `_build_progression_compare_response` to ensure proper handling of slot differences and quality scores, improving response clarity.
- Updated frontend components to reflect changes in rematch handling and evaluation logic.
- Bumped version to reflect the new features and improvements.
- Introduced `_annotate_slot_diffs` to mark trivial ID swaps in slot differences, improving clarity in comparison results.
- Added `_actionable_slot_diffs` to filter out non-actionable differences, streamlining the evaluation process.
- Implemented `_build_rematch_suggestion_diffs` to generate suggestions based on rematch logs, enhancing the path optimization workflow.
- Updated `_build_progression_compare_response` to incorporate actionable slot differences and rematch suggestions, improving the response structure.
- Enhanced frontend components to display rematch suggestions and handle trivial differences more effectively.
- Bumped version to reflect the new features and improvements.
- Introduced `_steps_to_evaluate_payloads` to convert path steps into evaluation payloads for improved quality assessments.
- Updated `_build_progression_compare_response` to include a new `proposed_eval` parameter, allowing for fair quality assessment comparisons.
- Enhanced `ProgressionGraphEditor` to utilize the new pipeline quality assessment data.
- Modified `ProgressionOptimizeCompareModal` to display detailed comparison results, including handling of trivial slot differences and optimization hints.
- Bumped version to reflect the new features and improvements.
- Updated `suggest_progression_path` to include additional evaluation parameters, allowing for more comprehensive path assessments.
- Introduced `PathQaPipelineDetails` component to display detailed quality assessment metrics, including rematch and refine logs, in the frontend.
- Enhanced `ProgressionGraphEditor` to manage proposed path evaluations and integrate quality assessment results into the draft workflow.
- Improved `ProgressionOptimizeCompareModal` to present optimization hints and quality tier information for proposed paths.
- Bumped version to reflect the new features and improvements.
- Added `compare_with_assignments` flag to `ProgressionPathSuggestRequest` to enable comparison of proposed paths with existing slot assignments.
- Introduced `_assignment_preservation_active` function to determine if existing assignments should be preserved during path suggestions.
- Enhanced `suggest_progression_path` to handle comparison logic, including validation for minimum slot assignments required for comparison.
- Implemented `_build_progression_compare_response` to structure the response for comparison results, including slot differences and quality scores.
- Updated frontend components to support new comparison features, including handling of slot assignments and optimization comparisons.
- Bumped version to reflect the new features and improvements.
- Updated `PROJECT_STATUS.md` to reflect the addition of the Planning AI Progression Graph and its context in the roadmap.
- Enhanced `DOMAIN_MODEL.md` with details on the new `planning_catalog_context` features, allowing trainers to manage curriculum stages and context.
- Added tests in `test_planning_catalog_context.py` to validate the separation of LLM highlights from fix hints during QA processes.
- Updated `HANDOVER.md` and `PLANNING_KI_ROADMAP.md` to reflect the latest app version and improvements in the planning context.
- Enhanced frontend components to support the new planning catalog context, including updates to `ExerciseProgressionPathBuilder` and `ProgressionGraphEditor`.
- Bumped version to 0.8.233 to reflect the new features and improvements.
- Introduced `planning_catalog_context` to `ProgressionPathSuggestRequest` for improved handling of catalog-related data during path suggestions.
- Implemented `_resolve_planning_catalog_context` to retrieve and validate the planning catalog context, enhancing the robustness of the suggestion process.
- Updated `_build_path_target_profile` to incorporate catalog context, enriching target profiles with relevant planning data.
- Enhanced frontend components in `ProgressionGraphEditor` to manage and display planning catalog context, including new selection options for focus areas, style directions, training types, and target groups.
- Added utility functions for parsing and transforming planning catalog context data for API interactions.
- Bumped version to 0.8.233 to reflect the new features and improvements.
- 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.
- 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 new functions for handling exercise visibility in progression graphs, including `library_content_visibility_for_progression_graph_sql` to manage visibility based on graph context.
- Added `_supplemental_exercise_ids_from_body` to extract exercise IDs from request bodies, improving data handling in path suggestions.
- Implemented visibility promotion candidate retrieval in the API, allowing for the identification of private exercises that need visibility adjustments when promoting graph visibility.
- Enhanced existing SQL queries and retrieval functions to incorporate new visibility logic, ensuring accurate exercise visibility based on user roles and graph settings.
- Updated frontend components to support visibility promotion workflows, including user prompts for managing private exercises during graph visibility changes.
- Added tests to validate new visibility logic and ensure robustness in exercise retrieval and promotion processes.
- 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.
- Added `semantic_brief_for_stage` function to enhance semantic briefs with stage learning goals for improved roadmap matching.
- Introduced `exercise_passes_stage_learning_goal_gate` to validate exercises against stage learning goals, enhancing relevance checks.
- Updated path retrieval and scoring logic to incorporate stage learning goals, allowing for more nuanced exercise selection.
- Enhanced UI to indicate weak matches with stage learning goals, improving user feedback on exercise relevance.
- 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.
- Introduced skills catalog management in the `ProgressionGraphEditor`, allowing for improved context in AI suggestions.
- Updated the loading mechanism to fetch both focus areas and skills catalog concurrently, enhancing performance.
- Implemented `ensureQuickCreateDraftFromAiSuggestion` utility to streamline the creation of drafts from AI suggestions.
- Enhanced slot management by integrating AI context into the gap fill preparation process, improving user experience.
- 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.
- Updated the `ProgressionGraphSlotEditorSpec.md` to reflect UI consolidation, removing separate editors and integrating functionalities into `ExerciseProgressionGraphPanel`.
- Refactored `ExerciseProgressionGraphPanel` to streamline the editing experience, removing unused state and logic for better performance.
- Enhanced `ProgressionGraphEditor` to support embedded usage and trigger callbacks on save, improving integration with other components.
- Simplified `ProgressionGraphEditPage` to redirect users to the exercises list with deep-linking support for selected graphs.
- 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.
- Introduced a primary chain selection in the Exercise Progression Graph Panel to streamline exercise path management.
- Updated the ProgressionChainEditor to support single path mode, allowing users to manage a single progression path more effectively.
- Enhanced the ExerciseProgressionPathBuilder with improved logic for merging graph nodes into path steps and filtering gap offers.
- Updated UI elements for better clarity and user experience, including new notifications and styling adjustments.
- Incremented application version to reflect these updates.
- Added `ProgressionChainEditor` to the Exercise Progression Graph Panel for improved management of exercise chains.
- Refactored state management to utilize `useRef` for chain editor references and removed unused sequence step logic.
- Introduced a path insert notice in the Exercise Progression Path Builder to inform users about unsaved changes.
- Updated UI elements to enhance clarity regarding the status of paths before saving.
- Incremented application version to reflect these updates.
- Introduced a new Planning Wizard Stepper component to guide users through the exercise planning process in four steps.
- Implemented logic to compute the maximum reachable step based on user input and current progress.
- Updated state management to track the current wizard step and ensure it aligns with user interactions.
- Enhanced the user interface to improve clarity and navigation through the planning stages.
- Incremented application version to reflect these changes.
- Incremented application version to 0.8.217 to reflect recent changes.
- Added support for a planning roadmap in the Exercise Progression Path Builder, allowing users to save and load structured planning artifacts.
- Enhanced the persistence logic for the planning roadmap, ensuring updates are correctly handled during graph modifications.
- Improved the user interface to display saved planning hints, enriching the user experience and interaction with the progression graphs.
- Incremented application version to 0.8.216 to reflect recent changes.
- Added skill expectations handling in the Exercise Progression Path Builder, improving the integration of expected skills into the roadmap steps.
- Enhanced the mapping of major steps to include load profiles, success criteria, anti-patterns, and exercise types, enriching the user experience and functionality.
- Added `stage_learning_goal_override` and `gap_trainer_supplements` parameters to `build_progression_path_gap_planning_context`, allowing for customized learning goals and additional trainer notes.
- Updated `gapOfferContextDisplayLines` to include trainer supplements in the context display.
- Enhanced `ExerciseProgressionPathBuilder` to utilize new parameters for improved gap fill offer handling.
- Incremented application version to 0.8.214 to reflect these changes.
- Added `context_preview` to the `build_gap_fill_offer` function, providing a structured overview of the roadmap snapshot.
- Introduced `gapOfferContextDisplayLines` utility to format context information for UI display, improving clarity for users.
- Updated `ExerciseProgressionPathBuilder` and related components to utilize the new context preview, enhancing the user experience.
- Incremented application version to 0.8.213 to reflect these changes.
- Introduced `build_progression_gap_snapshot` function to create a compact roadmap context for gap exercises, integrating start situation, target state, and stage specifications.
- Updated `build_gap_fill_goal_text` to include roadmap snapshot details, enhancing the context for AI-generated exercises.
- Enhanced `ProgressionPathSuggestRequest` and related components to support new structured inputs for start/target analysis, improving user experience and AI suggestions.
- Incremented application version to 0.8.212 to reflect these changes.
- Added `include_llm_start_target` option to `ProgressionPathSuggestRequest` for improved roadmap suggestions.
- Introduced new classes `StartTargetExtractArtifact` and `StartTargetResolveMeta` to handle LLM extraction results and metadata.
- Implemented `try_llm_start_target_extract` function to extract start and target states from goal queries using LLM.
- Updated `resolve_roadmap_structured_input` to prioritize user inputs, LLM extractions, and regex parsing for start/target resolution.
- Enhanced `ExerciseProgressionPathBuilder` to utilize new structured inputs and display extraction sources.
- Incremented application version to 0.8.211 to reflect these changes.
- Introduced `RoadmapStructuredInput` to encapsulate structured inputs for start situation, target state, and roadmap notes.
- Updated `ProgressionPathSuggestRequest` to include new fields for structured roadmap inputs.
- Implemented parsing logic for goal queries to extract start and target states, enhancing the goal analysis process.
- Enhanced `build_goal_analysis` to utilize structured inputs, improving the clarity and relevance of generated goals.
- Updated the `ExerciseProgressionPathBuilder` component to support new structured input fields, enhancing user experience.
- Incremented application version to 0.8.210 to reflect these changes.
- Introduced `roadmap_qa_mode` to manage QA behavior based on roadmap-first logic, improving gap detection between major steps.
- Updated `detect_path_gaps` to skip gaps for roadmap-planned neighbor pairs, enhancing the accuracy of path assessments.
- Added new helper function `is_roadmap_planned_neighbor_pair` to facilitate roadmap neighbor checks.
- Updated relevant tests to validate new functionality and ensure robustness.
- Incremented application version to 0.8.209 to reflect these changes.
- Added `planning_context` to the `suggestExerciseAi` endpoint, enabling structured planning context for new exercise creation.
- Updated relevant components and backend logic to handle the new planning context, enhancing the AI's exercise suggestion capabilities.
- Incremented application version to 0.8.208 to reflect these changes.
- Added support for editable major steps in the roadmap, allowing users to modify phase, learning goals, and order before exercise matching.
- Introduced a new `roadmap_override` feature to facilitate customized retrieval without re-invoking the roadmap AI.
- Updated the `ExerciseProgressionPathBuilder` component to incorporate these new features, enhancing user interaction and flexibility.
- Incremented application version to 0.8.207 to reflect these changes.
- Introduced logic to manage path capacity dynamically, allowing users to expand the maximum number of steps when inserting new offers.
- Implemented confirmation prompts for users when the path is full, enhancing user experience and decision-making.
- Updated the `ExerciseProgressionPathBuilder` component to reflect these changes, improving the handling of gap-fill offers and user interactions.
- Adjusted UI messages to clarify the implications of adding new steps and the conditions under which users can expand the path.
- Introduced a roadmap-first approach for retrieval, allowing for structured exercise suggestions based on stage specifications and major steps.
- Added functionality to generate gap-fill offers for unfilled roadmap stages, improving the relevance of exercise recommendations.
- Updated the `ExerciseProgressionPathBuilder` to support the new roadmap-first feature, enhancing user experience with clearer exercise paths.
- Incremented application version to 0.8.206 and updated the database schema version to reflect these changes.
- Introduced a roadmap-first approach for the planning AI, allowing for a structured progression graph that aligns with the overall project roadmap.
- Added new functionality to strip off-topic steps from exercise paths, improving the relevance of generated exercise suggestions.
- Implemented a detailed goal text generation for AI proposals, enhancing the context provided for new exercises.
- Updated the ExerciseProgressionPathBuilder component to support new features, including roadmap previews and improved focus area handling.
- Incremented application version to 0.8.205 and updated database schema version to 20260606086 to reflect these changes.
