- 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 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.
- 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.
- 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 a new target architecture document for the AI Prompt System, detailing context types, composition, and planning phases.
- Refactored the backend to utilize a shared function for loading AI prompt rows, reducing SQL duplication in the `exercise_ai` module.
- Incremented the application version to 0.8.159 and updated the changelog to reflect these changes, including enhancements to the AI prompt management and documentation links.
