- 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 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 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.
- Updated the AI gap filling logic to include structured offers for unfilled gaps, improving the user experience in the Exercise Progression Path Builder.
- Introduced new functions for detecting off-topic steps and parsing LLM-suggested exercises, enhancing the contextual relevance of exercise suggestions.
- Enhanced the frontend components to support new AI proposal features, including quick creation modals for newly suggested exercises.
- Incremented version to 0.8.190 and updated changelog to reflect these improvements in planning AI functionality.
- Replaced the manual path selection logic with a new `pick_best_path_hit` function to streamline the process of selecting the best exercise based on semantic scores and gating criteria.
- Updated the semantic gating logic to apply a soft penalty for off-topic exercises, improving the flexibility of exercise selection.
- Enhanced the handling of title, summary, and goal parameters in semantic checks to ensure more accurate relevance assessments.
- Incremented version to 0.8.189 and updated changelog to reflect these improvements in planning AI functionality.
- Updated the path selection logic to incorporate semantic gating, ensuring only relevant exercises are considered based on semantic scores.
- Introduced new functions for building path target profiles and resolving semantic skill weights, enhancing the contextual understanding of exercise suggestions.
- Improved the retrieval process by applying dynamic retrieval weights based on semantic strength, refining the accuracy of exercise recommendations.
- Incremented version to 0.8.188 and updated changelog to document these enhancements in planning AI functionality.
- Introduced path reordering functionality using LLM with `ordered_step_indices`, allowing for dynamic adjustment of exercise progression paths.
- Added AI gap filling capabilities, enabling the system to propose new exercises when unbridgeable gaps are detected.
- Updated the backend to support new request parameters for path reordering and AI gap filling.
- Enhanced frontend components to reflect these new features, including alerts for AI proposals and adjustments in exercise display.
- Incremented version to 0.8.187 and updated changelog to document these significant enhancements in planning AI functionality.
- Introduced new functions to load exercise goals and variant names in chunks, improving data retrieval efficiency.
- Integrated semantic scoring into the ranking logic, allowing for more nuanced exercise suggestions based on semantic relevance.
- Updated the planning exercise suggestion process to include semantic brief handling, enriching the context for exercise recommendations.
- Adjusted the retrieval phase to incorporate dynamic retrieval weights based on semantic strength, enhancing the overall suggestion accuracy.
- Incremented version to 0.8.186 and updated changelog to reflect these significant enhancements in planning AI 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.
