- 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.
- Incremented version to 0.8.184, reflecting the implementation of Phase C2 features.
- Added support for displaying variant lists and suggested variant names in exercise suggestions.
- Enhanced the ExercisePickerModal to allow selection of exercise variants and improved handling of variant IDs.
- Updated backend logic to enrich planning hits with variant metadata, ensuring accurate exercise variant selection.
- Documented changes in the changelog to highlight the new capabilities in planning AI functionality.
- Incremented version to 0.8.183, reflecting the implementation of Phase C1 enhancements.
- Added support for progression graph auto-matching and variant-aware successors in exercise suggestions.
- Updated request and response structures to include `anchor_exercise_variant_id`, `progression_graph_name`, and `suggested_variant_id`.
- Enhanced frontend components to integrate planning AI search capabilities, including a new modal for exercise creation and improved context display in the exercise list.
- Updated changelog to document these significant improvements in planning AI functionality.
- Introduced a new function `hybrid_ranking_ambiguous` to determine when to rerank candidates based on score proximity, improving the decision-making process for exercise suggestions.
- Updated `should_run_llm_rank_pipeline` to incorporate the new ranking logic and handle scenarios with ambiguous rankings more effectively.
- Adjusted the frontend to always include LLM ranking in requests, ensuring consistent behavior across different query lengths.
- Incremented version to 0.8.182 and updated changelog to reflect these enhancements in planning AI 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.
- Updated ExerciseAiQuickCreateOffer to set showSketchField to true by default and introduced sketchOptional prop for improved flexibility in exercise creation.
- Refactored ExercisePickerModal and ExercisesListPageRoot to leverage useExerciseAiQuickCreateFields hook, simplifying state management for quick create fields.
- Removed deprecated parsing logic and streamlined error handling for sketch input, enhancing user experience during exercise creation.
- Improved placeholder text and labels for clarity, ensuring better guidance for users when providing input for AI-generated exercises.
- Updated APP_VERSION to 0.8.166 and modified BUILD_DATE to reflect recent changes.
- Enhanced AI exercise creation process with a new quick create feature, allowing users to generate exercises based on search input.
- Introduced a rich text editor for editing AI-generated drafts, improving user experience in exercise creation.
- Updated ExercisePickerModal and related components to support the new quick create functionality, including error handling and input validation.
- Added new utility functions for parsing search queries and building exercise payloads from drafts.
- Updated the quick create process to include a preview feature for AI-generated exercises, allowing users to review goals, execution, preparation, and trainer notes.
- Introduced new constants for instruction fields and refactored the payload building function to utilize the preview data.
- Improved error handling to ensure at least one of the goal or execution fields is populated.
- Deprecated the previous payload building function in favor of the new preview-based approach, streamlining the exercise creation workflow.
- Updated APP_VERSION to 0.8.164 and added changelog entry for the new version.
- Enhanced ExercisePickerModal to support quick exercise creation using AI, including fields for sketch and focus area.
- Implemented error handling for AI suggestions and improved user prompts for input validation.
- Updated UI elements to reflect changes in exercise creation workflow.
- Replaced hardcoded visibility labels with the new constant EXERCISE_VISIBILITY_FIELD_LABEL in multiple components, ensuring consistent terminology throughout the application.
- Updated UI text to reflect the change from "Sichtbarkeit" to "Freigabelevel" in various contexts, enhancing clarity for users.
- Improved accessibility by standardizing the visibility-related labels in the ExercisePickerModal, ExerciseProgressionGraphPanel, and other related components.
- Introduced new `SkillTreeSelect` and `SkillTreeMultiSelect` components for enhanced skill selection in various modals and forms.
- Updated API calls to use `listSkillsCatalog` instead of `listSkills` for improved data retrieval.
- Enhanced CSS styles for skill selection components to improve user experience and visual consistency across the application.
- Bumped APP_VERSION to 0.8.119 and updated the changelog to reflect new features.
- Introduced the ExerciseListCard component and implemented lazy loading for the Progression Tab using React's Suspense.
- Enhanced the ExercisePickerModal with virtualization for improved performance using @tanstack/react-virtual.
- Updated documentation to reflect the new app version and its corresponding changes.
- Bumped APP_VERSION to 0.8.115 and updated the changelog to reflect changes, including the introduction of keyset pagination for the GET /api/exercises endpoint.
- Enhanced the exercises router to support cursor-based pagination using cursor_updated_at and cursor_id, improving performance and user experience.
- Updated frontend components to utilize the new pagination method, removing offset-based loading logic.
- Bumped app version to 0.8.100, reflecting recent updates.
- Improved validation logic for combination exercises in the backend, ensuring proper handling of exercise variants.
- Enhanced frontend components, including the ExercisePickerModal, to support filtering and displaying combination exercises.
- Updated API payloads and utility functions to accommodate new exercise types and their properties.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated app version to 0.8.99, reflecting the addition of combination exercises.
- Implemented new data structures and validation for combination slots and archetypes in the backend.
- Enhanced frontend components to support selection and display of combination exercises, including new UI elements for managing slots and archetypes.
- Updated API payload handling to accommodate new exercise types and their associated data.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Introduced a quick create draft feature allowing users to create private exercise drafts directly from the ExercisePickerModal.
- Added state management for quick create inputs including title and summary, with validation for minimum title length.
- Updated the Dashboard to display a preview of private exercise drafts, enhancing user visibility of pending exercises.
- Enabled quick create functionality in TrainingFrameworkProgramEditPage and TrainingPlanningPage for streamlined exercise management.
- Introduced new filtering options for style directions, training types, and target groups in the exercise list.
- Implemented catalog rule picker components to manage inclusion and exclusion of exercise attributes.
- Updated utility functions to handle new catalog rules for improved filtering logic.
- Enhanced the ExercisesListPage and ExercisePickerModal to support the new filtering features, improving user experience.
- Bumped application version to 0.8.40 and updated module versions accordingly.
- Introduced new focus area filtering options in the ExercisesListPage, allowing users to include or exclude exercises based on specified focus areas.
- Added utility functions for deduplicating and merging focus area IDs to improve filtering logic.
- Enhanced the ExercisePickerModal and ExercisesListPage components to support new focus rules and improve user experience with focus area selections.
- Introduced new function `club_admin_shares_club_with_creator` to check club admin permissions for shared clubs.
- Updated `can_manage_club_org` to incorporate new role checks.
- Enhanced exercise deletion logic to include checks for club admin roles and shared club memberships.
- Added new filters for exercise visibility and status in the ExercisesListPage, allowing users to exclude specific criteria.
- Implemented functionality to save user-specific exercise list preferences, improving user experience.
- Updated API interactions to support new filtering options and preferences for exercise management.
- Updated ExercisePeekModal to support exercise variants, improving user experience when selecting exercises.
- Enhanced ExercisePickerModal with multi-select functionality, allowing users to select multiple exercises at once.
- Introduced drag-and-drop support for reordering training unit sections in TrainingUnitSectionsEditor, enhancing organization and usability.
- Improved TrainingFrameworkProgramEditPage and TrainingPlanningPage to manage exercise selection and section movement across slots more effectively.
- Added new CSS styles in app.css for better visual feedback during drag-and-drop actions and improved layout consistency.
- Introduced ExercisePickerModal for selecting exercises and their variants.
- Updated state management to handle exercise titles and variants in training units.
- Implemented enrichSectionsWithVariants function to fetch and integrate exercise details from the server.
- Improved loading logic for training units to include exercise variant data, enhancing user experience in planning sessions.
