- Added `SHINKAN_AI_DEBUG` environment variable to `.env.example`, enabling detailed logging for AI operations in Docker containers.
- Integrated `SHINKAN_AI_DEBUG` into both `docker-compose.dev-env.yml` and `docker-compose.yml` to facilitate debugging during development and production environments.
- Introduced detailed logging for AI operations in the `exercise_ai` and `openrouter_chat` modules, activated by the `SHINKAN_AI_DEBUG` environment variable, to aid in debugging and performance monitoring.
- Updated the `run_exercise_ai_suggestion` function to log prompt lengths, response sizes, and JSON parsing errors, enhancing transparency in AI interactions.
- Improved the `_flatten_message_content` function to handle nested content structures more effectively, ensuring compatibility with various AI response formats.
- Incremented the application version to 0.8.157 and updated the changelog to reflect these enhancements, including new logging features and content handling improvements.
- Added a new function `_first_balanced_json_array` to extract the first complete top-level JSON array from arbitrary text, enhancing robustness in parsing.
- Updated the `run_exercise_ai_suggestion` function to raise clear HTTP exceptions for empty responses from the OpenRouter, ensuring better error handling.
- Introduced `_flatten_message_content` in the `openrouter_chat` module to handle structured message content from OpenAI, improving compatibility with various content formats.
- Incremented the application version to 0.8.156 and updated the changelog to reflect these enhancements, including improved error messages and JSON parsing capabilities.
- Introduced a new constant `_MAX_SANITIZE_SKILL_INPUT_ROWS` to limit the number of skill entries processed, improving performance and preventing issues with excessively long skill arrays.
- Updated the `_extract_json_array` and `_sanitize_skill_entries` functions to enforce this limit, ensuring that only a maximum of 250 skill entries are handled and that processing stops after 5 valid entries.
- Incremented the application version to 0.8.155 and updated the changelog to reflect these changes, including a note on the improvements made to the AI endpoint for skill arrays.
- 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 AI Exercise Implementation Plan to include a detailed description of the new suggestion dialog for AI proposals, allowing users to preview and selectively adopt AI-generated summaries and skills.
- Implemented a new preview feature in the ExerciseFormPageRoot component, enabling users to review AI suggestions before applying them to the form.
- Enhanced the skill management process by normalizing AI-suggested skills and integrating them into the exercise form, improving user interaction and data handling.
- Incremented the version number from 0.2 to 0.3 in the AI Training Planning document to reflect the latest changes.
- Added a new reference to the `working/AI_PLANNING_KI_MULTISTAGE_FORECAST.md` document, outlining the architecture preview for the planning AI.
- Updated the changelog in `backend/version.py` to include the latest version entry, ensuring accurate tracking of changes.
- 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.
