- 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.
- 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.
- 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 a new environment variable `CLUB_FEATURE_ENFORCE` to control club feature access, allowing values of 1, true, or yes for activation.
- Updated the backend logic to check for club feature enforcement, raising HTTP exceptions when access is denied without an active club context.
- Enhanced the admin rights router with a new endpoint to check the enforcement status of club features.
- Incremented application version to 0.8.202 to reflect these changes.
- Updated the capability catalog to reflect a registry-first approach, requiring modules to register rights and quotas upon implementation.
- Enhanced the backend to synchronize the rights registry with the database, ensuring only registered capabilities and features are displayed in the admin matrix.
- Modified SQL queries in the admin rights router to filter capabilities and features based on module registration.
- Updated documentation to clarify the new rights and features registry process, replacing the previous catalog-first method.
- Incremented application version to 0.8.201 and updated database schema version to 20260606084 to reflect these changes.
- Updated the Membership RBAC Decisions document to reflect the latest implementation status and roadmap, including new features and enhancements.
- Incremented application version to 0.8.200 and updated database schema version to 20260606083.
- Added a new API endpoint to clear capability grants for club roles, improving admin rights management.
- Enhanced the Admin Rights page in the frontend to display enforcement status and feature consumption details for capabilities.
- Improved the user interface for better clarity on rights and capabilities management.
- Introduced the `consume_club_feature_with_usage` function to standardize feature consumption across endpoints, improving code reusability and clarity.
- Implemented `merge_feature_usage_into_response` to embed feature usage data in API responses, streamlining frontend integration.
- Updated various backend routers to utilize the new consumption logic, ensuring consistent feature usage tracking during AI-related actions.
- Enhanced tests to validate the new consumption and logging behavior.
- Incremented application version to 0.8.199 and updated module version for 'club_features' to 1.6.0 to reflect these changes.
- Replaced the admin club feature exemptions router with a new admin rights router to streamline capability management.
- Added new API endpoints for managing admin rights, including capability grants and quota bypass for portal roles and profiles.
- Updated the frontend to include navigation and lazy loading for the new Admin Rights page.
- Incremented application version to 0.8.197 to reflect these changes and enhancements.
- Added support for club feature quota bypass based on portal roles and profile grants in the capabilities check.
- Introduced new functions to handle quota bypass logic in club feature access and consumption.
- Updated the FeatureUsageBadge component to reflect platform exemptions for features.
- Incremented application version to 0.8.195 and database schema version to 20260606083 to reflect these changes.
- Enhanced backend routers to include new logic for consuming club features during AI-related actions.
- Incremented application version to 0.8.192 and database schema version to 20260606081.
- Updated club module versions for 'clubs' and 'club_creation_requests' to reflect recent changes.
- Implemented logic to mark approved club creation requests as 'superseded' when the associated club is deleted.
- Refactored frontend components to clear session storage for coach-related keys upon logout and during login checks.
- Enhanced onboarding page to accurately display the status of club creation requests based on their validity.
- Introduced endpoints for managing club creation requests, including fetching, creating, and withdrawing requests.
- Updated the onboarding page to allow users to submit new club creation requests and view their existing requests.
- Enhanced the admin interface with navigation and routing for club creation requests management.
- Incremented version to 0.8.191 to reflect these new features and updates in the application.
- Introduced `email_verified` and `account_state` attributes in the `TenantContext` to improve user state management.
- Updated the `resolve_tenant_context` function to dynamically fetch `email_verified` status from the database and determine `account_state` based on user roles and memberships.
- Implemented `assert_min_account_state` checks across various endpoints to enforce access control based on user account status.
- Incremented version to 1.1.0 in version.py to reflect these enhancements in tenant context management and access control.
- Introduced `probe_club_feature_access` to check club feature limits and log access attempts without blocking by default.
- Added `_live_inventory_count` function to retrieve current counts for specific features, enhancing feature limit management.
- Updated various endpoints to utilize the new probing functionality, ensuring compliance with club feature access rules.
- Incremented version to 1.1.0 in version.py to reflect these enhancements in club feature management.
- Introduced a new admin user content management endpoint for superadmins, allowing for moderation of user-generated content.
- Updated the backend to include new API functions for retrieving, patching, and deleting user content items.
- Enhanced the frontend with a new Admin User Content page and navigation link for easy access to user content management.
- Updated access layer documentation to reflect the new endpoint and its exempt status.
- Incremented version to 0.8.191 and updated changelog to document these additions in admin functionality.
- Incremented version to 0.8.185, reflecting the implementation of Phase C3 features.
- Introduced the `POST /api/planning/progression-path-suggest` endpoint for generating exercise progression paths.
- Enhanced the ExerciseProgressionGraphPanel with a new ExerciseProgressionPathBuilder for reviewing and saving paths.
- Updated changelog to document the new capabilities in planning AI functionality.
- 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.
- 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.
- 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.
- Added `exercise_instruction_rewrite` functionality to enhance AI-generated instructions, incorporating fields for goal, execution, preparation, and trainer notes.
- Updated `ExerciseFormAiPromptContext` to include new fields and methods for instruction handling.
- Enhanced the `run_exercise_form_ai_suggestion` function to support instruction rewriting and validation.
- Modified API endpoints and frontend components to integrate instruction features, including a new button for AI instruction revision.
- Incremented application version to 0.8.163 and updated changelog to reflect these changes, including migration details and new functionality.
- Introduced `ExerciseFormAiPromptContext` for unified handling of prompt-related data, enhancing the admin preview and exercise API.
- Added `run_exercise_form_ai_suggestion` function to streamline AI suggestion processing, integrating with the OpenRouter.
- Updated various modules to utilize the new context model, improving code clarity and reducing redundancy.
- Incremented application version to 0.8.162 and updated changelog to reflect these changes, including migration details and new functionality.
- Added `openrouter_model` field to the `ai_prompts` table, allowing for optional model overrides per prompt.
- Updated the `exercise_ai` module to utilize the effective OpenRouter model based on prompt-specific settings, enhancing flexibility in AI interactions.
- Enhanced the admin interface to support OpenRouter model configuration for prompts, improving usability for Superadmins.
- Incremented application version to 0.8.161 and updated changelog to reflect these changes, including migration details and new functionality.
- Introduced `load_and_render_ai_prompt` and `render_ai_prompt_template_for_row` in `ai_prompt_runtime` to streamline prompt loading and rendering processes.
- Added `AiPromptUnavailableError` for better error handling when prompts are inactive or missing.
- Created `ai_prompt_job` module with `ExerciseFormAiPromptContext` and `resolve_exercise_form_variables` to support admin preview functionality.
- Updated documentation and target architecture to reflect changes in the AI prompt system.
- Incremented application version to 0.8.160 and updated changelog accordingly.
- Added the `matrix_editor` endpoint to the ACCESS_LAYER_ENDPOINT_AUDIT.md, specifying its access requirements and exempt status for superadmins.
- Updated comments in the `matrix_editor.py` file to clarify its role as a superadmin tool and its access restrictions.
- Included the `matrix_editor.py` in the EXEMPT_ROUTERS list in the access layer hints script, ensuring proper access control documentation.
- Added new functionality for exporting and importing matrix editor data in JSON and CSV formats within the MaturityMatrixToolsAdmin component.
- Updated the API utility functions to support matrix editor exports and imports, enhancing the backend communication for Superadmin tasks.
- Refactored the client API to streamline request handling and improve code clarity.
- Included new UI elements for file upload and download actions, improving user experience in managing matrix data.
- Incremented version to 1.1 and updated the status to reflect the implementation of core features including `ai_prompts`, `prompt_resolver`, and the Superadmin HTTP API.
- Documented the current API endpoints for managing AI prompts, including CRUD operations and preview functionality.
- Introduced a new placeholder catalog and preview capabilities for the Superadmin interface.
- Enhanced the backend with new functions for handling AI prompt templates and integrated them into the API.
- Updated frontend components to include navigation and routing for the new Admin AI Prompts page.
- Incremented application version to 0.8.158 and updated changelog to reflect these changes.
- Added documentation for the new Superadmin CRUD endpoints for managing AI Skill Retrieval Profiles (`/api/admin/ai-skill-retrieval-profiles*`).
- Updated the ACCESS_LAYER_ENDPOINT_AUDIT.md to include the new Superadmin API and its exempt status.
- Registered the ai_skill_retrieval_admin router in the backend and updated versioning to reflect the changes.
- Enhanced the frontend with a new Admin page for AI Skill Retrieval, including navigation and API integration for profile management.
- Introduced migration 068 for `ai_skill_retrieval_profiles`, enabling configurable weights and quotes for skill catalog prioritization in exercise AI suggestions.
- Updated the `POST /api/exercises/ai/suggest` endpoint to include an optional `focus_areas_context` field, allowing for enhanced context in AI-generated suggestions.
- Enhanced the `exercise_ai` module to utilize context-based skill selection, incorporating scoring, category caps, and keyword patches for improved AI responses.
- Updated the ExerciseFormPageRoot component to pass focus area context to the AI suggestion API, streamlining user interaction with AI-generated content.
- Incremented version numbers in `backend/version.py` to reflect the latest changes and ensure accurate tracking in the changelog.
- Updated the exercise form to include a tabbed navigation structure, improving user experience with sections for Stammdaten, Anleitung, Einordnung, Varianten, and Medien & Mehr.
- Introduced the concept of **Freigabelevel** (visibility level) in the UI, replacing previous terminology for clarity and consistency across components.
- Implemented new AI endpoints for exercise suggestions and regeneration, allowing for dynamic content generation without direct database writes.
- Removed the legacy `is_primary` flag from exercise skills in the UI, ensuring that intensity levels (`niedrig`, `mittel`, `hoch`) are the primary focus for skill management.
- Enhanced the variant management process with improved saving mechanisms and UI updates to reflect changes more intuitively.
- Added capabilities for weighted skill profiles, allowing trainers to compare training modules, frameworks, and regression paths based on skill contributions.
- Updated the skill scoring specification to include peer context separation and list filtering, ensuring accurate comparisons among visible artifacts of the same type.
- Enhanced the API to support batch summaries for skill profiles and discovery suggestions, improving data retrieval efficiency.
- Refactored frontend components to display skill metrics, including scores and peer percentages, with improved filtering options for better user experience.
- Updated documentation to reflect the latest changes and enhancements in the skill scoring system.
- Introduced new helper functions for managing artifact type corpus, improving code organization and readability.
- Updated the `compute_club_corpus_reference` function to utilize the new corpus handling methods, enhancing clarity and maintainability.
- Refactored skill profile functions to leverage the new corpus structure, ensuring consistent data retrieval across different artifact types.
- Improved the handling of visibility clauses for library content, streamlining database queries for skill profiles.
- Enhanced the batch skill profile summary function to aggregate reference data by artifact type, improving performance and accuracy.
- Modified the `compact_profile_summary` function to allow for dynamic skill and category limits, enhancing flexibility in profile data retrieval.
- Updated frontend components to display skill weights and scores more effectively, improving user interaction with skill metrics.
- Adjusted CSS styles for skill KPI tiles to better differentiate between score and percentage displays, ensuring a clearer visual representation.
- Refactored utility functions to streamline skill summary handling, enhancing overall code maintainability and performance.
- Updated the skill scoring specification to include club-specific metrics and improved aggregation methods for skill profiles.
- Introduced new API endpoints for batch skill profile summaries, allowing for efficient retrieval of compact skill data.
- Enhanced frontend components to display skill profiles with club comparisons, improving user interaction and visibility of skill strengths.
- Added filtering options for skills in the framework programs, enabling users to refine selections based on training weight relative to club maximums.
- Improved CSS styles for skill profile displays, ensuring a cohesive and user-friendly interface across the application.
- Enhanced the skill scoring system with category grouping and a universal scale for improved comparability across programs.
- Introduced new calculations for artifact share percentage and universal percent, allowing for a more nuanced understanding of skill contributions.
- Updated the API to reflect changes in the skill profile structure, including main category and top skill details.
- Improved frontend components to display skills by main category, enhancing user experience in skill discovery and profile visualization.
- Adjusted tests to validate the new scoring logic and ensure accurate representation of skills and their weights.
- Updated the framework program documentation to reflect the completion of Phase 3 v1.0, including new skill scoring and API enhancements.
- Added new API endpoints for skill profile retrieval and suggestions, improving the ability to aggregate and display skills based on training data.
- Introduced new UI components for skill profiles and discovery in the frontend, enhancing user interaction with training frameworks and skills.
- Updated version information to 0.8.151, reflecting the addition of skill profiles and related features.
- Added SQL aggregations for session duration (min/max) and goal titles in the training framework programs query.
- Updated the TrainingPlanningFrameworkImportModal component to include filtering options for focus areas, training types, and target groups.
- Implemented session duration display in the TrainingFrameworkProgramsListPage, improving user visibility of program details.
- Introduced utility functions for formatting session duration ranges, enhancing the overall user experience in training planning.
- Bumped application version to 0.8.150 and updated build date and database schema version.
- Introduced new SQL migration for planned duration fields in training units and sections.
- Added functions to handle focus areas and style directions in training framework programs.
- Enhanced training planning components to support planned duration input and display.
- Updated frontend components to manage and display planned duration for training units and sections.
- Updated the `list_exercises` function to include counts for exercise variants and media, improving data retrieval for exercise details.
- Added new CSS styles for the exercise card footer to display variant and media statistics in a visually appealing manner.
- Implemented `ExerciseCardContentStats` component to conditionally render variant and media counts, enhancing the user interface of exercise cards.
- Incremented app version to 0.8.148 and updated changelog to reflect new features.
- Improved the training plan template structure by adding a preview of sections, including support for split sessions.
- Introduced a new editing page for training plan templates, allowing users to modify templates directly.
- Enhanced the TrainingPlanningPageRoot to include a description field when saving templates, improving user guidance.
- Updated permissions to allow editing of training plan templates based on user roles.
- Incremented app version to 0.8.146 and updated build date to 2026-05-19.
- Added new API endpoint to publish training units as session blueprints to framework programs.
- Introduced frontend functionality to support publishing training units, including a modal for user interaction.
- Updated changelog to reflect the new feature and its associated changes.
- Introduced `_normalize_mw_category` function to clean category names for API calls, ensuring consistent handling of category prefixes.
- Updated `SmwClient` methods to utilize normalized category names, improving data retrieval accuracy.
- Added `_wiki_category_or_default` function to provide default categories based on import type, enhancing user experience during imports.
- Integrated new fields `karate_relevance` and `relevance_level` into various admin components, allowing for better skill management.
- Incremented app version to 0.8.145 and updated changelog to reflect these changes.
- Added `karate_relevance` and `relevance_level` fields to the SkillCreate and SkillResponse models, allowing for more detailed skill attributes.
- Updated the SMW property mapping to include these new fields, facilitating their integration during data import.
- Implemented parsing logic for relevance levels from Wiki data, ensuring proper handling of values between 1 and 3.
- Modified the upsert and create skill functions to support the new fields, ensuring they are correctly stored and updated in the database.
- Incremented app version to 0.8.143 and updated changelog to reflect these changes.
- Introduced new functions for managing edit, delete, and governance transition permissions for library content, aligning with role-based access control (RBAC) principles.
- Updated existing routers to utilize these new functions, ensuring consistent permission checks across training frameworks, modules, and progression graphs.
- Enhanced visibility and governance handling for training plan templates and library content, improving overall content management and user experience.
- Incremented app version to 0.8.142 and updated changelog to reflect these changes.
- Incremented app version to 0.8.141 and updated build date to 2026-05-14.
- Modified the planning module version to 0.12.0, improving template section handling with phase metadata.
- Introduced new functions for normalizing and inserting training plan template sections, ensuring accurate phase representation during saves.
- Updated frontend components to utilize new utility functions for managing training plan templates, enhancing user experience and data integrity.
- Updated backend logic to include phases in training unit hydration and insertion processes, improving data integrity.
- Modified frontend components to support phases in training framework slots, ensuring consistent data representation.
- Refactored payload building functions to accommodate phases, enhancing the save functionality for training plans.
- Improved user interface to enable controls for parallel phases, optimizing the user experience during training program edits.
- Updated the backend logic to ensure strict ordering of phase indices, preventing UNIQUE constraint violations when phases are duplicated.
- Enhanced the TrainingUnitSectionsEditor component with new state management for editing phase titles and stream names, improving user interaction.
- Implemented conditional rendering for input fields to facilitate inline editing of phase titles and stream names, streamlining the editing process.
- Bumped APP_VERSION to 0.8.138 and updated the changelog to reflect recent changes.
- Enhanced training unit planning with support for POST/PUT requests including phases and parallel streams.
- Fixed role assignment validation for stream co-trainers and added integration tests for phase handling.
- Updated the training planning API to improve data structure and retrieval for nested phases and sections.
- Bumped APP_VERSION to 0.8.137 and updated the changelog to reflect recent changes.
- Introduced Migration 063 for training unit phases and parallel streams, enhancing the structure of training units.
- Updated the training planning API to support nested phases and sections, improving data retrieval for UI components.
- Enhanced section handling to accommodate new phase and stream structures, ensuring compatibility with existing workflows.
