- Introduced new endpoints for updating training category and type parameters in the backend.
- Added corresponding update functions in the frontend API utility.
- Enhanced the Admin Activity Attribute Profiles page to support editing and saving changes for category and type parameters.
- Implemented state management for editing parameters and improved error handling during updates.
- Added new Admin UI for managing Activity Attribute Profiles.
- Enhanced ActivityPage to support dynamic loading and editing of session metrics.
- Updated API utility functions to handle new endpoints for training parameters and metrics.
- Improved form handling for session metrics, including validation and error management.
- Updated documentation to reflect new features and changes in session metrics handling.
Backend:
- workflow_executor.py: Add progress_callback parameter, emit events for execution_started, node_complete, execution_complete, execution_failed
- prompt_executor.py: Thread progress_callback through execute chain
- routers/prompts.py: New /execute-stream endpoint with asyncio Queue for SSE
Frontend:
- utils/api.js: New executeUnifiedPromptStream() function with EventSource
- pages/Analysis.jsx: Use SSE with live progress display (X/Y Nodes)
Fixes:
- No more gateway timeouts for complex workflows (10+ nodes)
- Live progress feedback for users
- Unlimited workflow complexity
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
- Introduced `ExpandableCollapsible` component to manage the visibility of lengthy content, allowing users to toggle between expanded and collapsed views.
- Updated `renderTestOutput` to utilize the new component for displaying test results, JSON outputs, and object representations, enhancing user experience by reducing clutter.
- Enhanced `Markdown` component to support fenced code blocks, improving the rendering of code snippets with language labels and better styling.
These changes improve the readability and organization of content within the application, providing users with a more interactive and manageable interface.
- Updated StartNode to display a trimmed analysis title if available, falling back to the label or 'Start'.
- Refactored WorkflowEditorPage to include analysis metadata (title, description, category) in the start node configuration.
- Improved serialization and deserialization of workflow graphs to handle new analysis fields.
- Enhanced user interface to allow setting and displaying analysis metadata for better clarity in the workflow editor.
These changes improve the user experience by providing clearer metadata handling in workflows and ensuring consistent display in analysis components.
- Introduced a new utility function to streamline the extraction of user-facing content from aggregated workflow results.
- Updated backend prompt handling to utilize the new function for improved clarity and maintainability.
- Adjusted frontend analysis component to leverage the utility for consistent content display across different workflow result formats.
These changes enhance the overall user experience by ensuring more reliable and readable output from workflow executions.
- Introduced a new endpoint for validating CSV templates without saving, allowing users to check field mappings and type conversions.
- Updated the `create_system_template` and `update_system_template` functions to include validation reports in responses.
- Enhanced error handling in CSV import processes by integrating `enrich_row_error` for more informative error messages.
- Improved the AdminCsvTemplateEditorPage to support format checking and display validation results, enhancing user experience.
- Incremented version numbers for `csv_import` and `admin_csv_templates` to reflect these updates.
- Implemented a new endpoint for diagnosing CSV imports without writing to the database, allowing users to validate mappings and type conversions.
- Introduced the `diagnose_vitals_row` function to analyze vital metrics and provide detailed feedback on data validity.
- Enhanced the CSV import logic to include alias handling for vital fields, improving compatibility with different CSV formats.
- Updated the frontend to support the new diagnosis feature, including UI elements for displaying diagnosis results and error details.
- Added tests to ensure the correctness of the new diagnosis functionality and its integration with existing import processes.
- Added new functions for calculating header signature recall and ranking metrics, improving the analysis of CSV templates.
- Updated existing CSV analysis endpoints to utilize the new ranking metrics, enhancing the accuracy of template matching.
- Refactored related code to replace Jaccard score calculations with the new metrics, providing a more comprehensive evaluation of CSV structure.
- Improved documentation for new functions to clarify their purpose and usage in the context of CSV template analysis.
- Added a new endpoint for analyzing uploaded CSV files, providing suggestions for field mappings and type conversions.
- Implemented validation for required field targets to ensure all mandatory fields are mapped correctly.
- Enhanced the admin CSV templates interface with new routes and navigation options in the frontend.
- Updated API utility functions to support the new CSV analysis functionality.
- Improved error handling for CSV uploads, including file size and row count checks.
- Bumped version of csv_import to 0.3.0, reflecting new analysis capabilities.
- Modified analyze_csv endpoint to allow optional module filtering, improving flexibility in template selection.
- Enhanced the import process to support both system and user-defined templates, ensuring backward compatibility.
- Updated frontend to streamline mapping choices and improve user experience during CSV analysis and import.
- Added detailed error handling and user feedback for import operations.
- Updated the function name from importCsv to importUniversalCsv to better reflect its purpose.
- Added documentation comment to clarify the parameters used in the universal CSV import process.
- Updated version for csv_import to 0.2.0, reflecting new features.
- Implemented a new POST endpoint for universal CSV import, supporting nutrition, weight, and blood pressure modules.
- Added CSV parsing function to yield rows as dictionaries for easier data handling.
- Enhanced error handling and logging for import operations.
- Introduced tests for the new CSV parsing functionality to ensure reliability.
- Added permissions for editing and deleting CSV field mappings.
- Created type converter for CSV cells to handle various data types.
- Implemented database migrations for CSV field mappings and import logs.
- Seeded initial system templates for nutrition and activity data imports.
- Developed admin endpoints for managing system CSV templates.
- Introduced user endpoints for CSV import analysis and mapping retrieval.
- Added tests for core CSV parser functionalities, including delimiter detection and value conversion.
Root Cause:
- Frontend serialized as "questions"
- Backend expected "question_augmentations"
- Analysis Nodes WITH questions configured sent empty array to backend
- Questions were never added to LLM prompt
Frontend workflowSerializer.js:
- Serialization: questions → question_augmentations (Backend field name)
- Deserialization: question_augmentations → questions (Frontend data object)
- Backward compatible: Falls back to "questions" for old workflows
Backend workflow_executor.py:
- Removed incorrect load_prompt_questions() function (was a misunderstanding)
- Back to original logic: Only use node.question_augmentations
- Simplified normalization logging
Impact:
- Analysis Node questions are now correctly sent to backend
- Questions augment the base prompt as intended
- LLM receives structured questions
- Decision signals are generated and accessible as placeholders
Example:
- Node configures question with id="q21"
- Signal becomes accessible as {{ node_2.signal_q21 }}
- Can be used in Logic Nodes and End Node templates
Issue: Workflow questions not sent to LLM (field name mismatch)
Version: 0.9p (workflow module)
Part 3: End Node Template Engine - Critical Fix
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Added new API endpoints for listing and updating widget-feature assignments, allowing for custom feature requirements.
- Introduced a new admin page for managing widget-feature assignments, enhancing the admin interface.
- Updated navigation to include a link to the new widget-feature assignments page.
- Refactored widget access logic to support AND-based feature requirements for widgets.
- Bumped app_dashboard version to 1.11.0 to reflect these changes and improvements.
- Added new API endpoints for managing the product dashboard standard, including retrieval, update, and deletion functionalities.
- Enhanced the DashboardConfigurePage to support admin mode for configuring the product dashboard standard.
- Updated the admin navigation to include a link for the product dashboard standard configuration.
- Refactored the dashboard layout logic to utilize the new product standard management features.
- Bumped app_dashboard version to 1.10.0 to reflect these enhancements and changes.
- Added functions to handle Apple Health sleep data in both segment and summary formats.
- Implemented robust error handling for date parsing and data conversion.
- Updated documentation to reflect new CSV format support and data aggregation logic.
- Bumped version in version.py to reflect the changes in the activity module.
- Integrated a new API endpoint for fetching the widget catalog in the Dashboard-Lab.
- Updated the dashboard layout schema to utilize the widget catalog for dynamic widget management.
- Refactored DashboardLabPage and PilotVizPage to leverage the new widget rendering system.
- Removed deprecated widget metadata from the frontend, streamlining the widget management process.
- Bumped app_dashboard version to 1.1.0 to reflect the new features and improvements.
- Added new routes and API endpoints for the Dashboard-Lab layout in the app.
- Updated main.py to include the app_dashboard router for backend integration.
- Enhanced App.jsx to include a route for the DashboardLabPage.
- Modified SettingsPage to add a link to the new Dashboard-Lab layout, improving user access to dashboard features.
- Updated version.py to reflect the new app_dashboard module version.
- Introduced a new API endpoint for fetching a summary of profile reference values, providing the latest and previous entries for each reference type.
- Updated ProfileReferenceValuesPage to display summary tiles with trend indicators for better user insights.
- Enhanced CSS for responsive layout of reference value tiles, improving the overall user experience on different screen sizes.
- Implemented trend calculation logic to visually represent changes between the latest and previous reference values.
- Added a new API endpoint for reordering reference value types based on user-defined order.
- Updated the AdminReferenceValueTypesPage to allow users to reorder types using up/down buttons.
- Introduced a consistent confidence level sorting mechanism across the application.
- Refactored related components to remove unused sort order fields and improve user experience.
- Updated the backend to include new fields for validation rules and metadata in reference value types.
- Enhanced the AdminReferenceValueTypesPage to support new validation rules for different data types.
- Improved the ProfileReferenceValuesPage to handle validation and metadata for profile reference values.
- Added API endpoint for fetching reference value metadata enums to support frontend validation.
- Refactored frontend forms to incorporate new fields and validation logic for a better user experience.
- Added new routes and API endpoints for managing reference value types in the admin section.
- Updated the frontend to include navigation and components for reference value types management.
- Enhanced the backend to support the new reference value types in the data layer and versioning.
- Introduced new routes and API endpoints for managing personal reference values.
- Updated the SettingsPage to include a section for reference values with navigation to manage them.
- Enhanced the backend to support reference values in the data layer and versioning.
- Added necessary imports and UI components for a seamless user experience.
- Added endpoints for listing and updating focus area usage types in the backend.
- Enhanced the AdminFocusAreasPage to display and manage allowed usage types for focus areas.
- Introduced a new state for usage types catalog and integrated it into the focus area editing process.
- Updated API utility functions to support new usage types operations.
Bug:
- Analysis nodes showed "Prompt #7edc6d6b-6cd5..." in canvas
- After re-selecting prompt, showed readable name "Pipeline: Ernährungs-Analyse"
- After loading workflow, showed UUID again
Root Cause:
- Serializer saved only prompt_id, not prompt_name
- Deserializer expected prompt_name but got null
- AnalysisNode fallback logic: data.prompt_name || `Prompt #{prompt_id}`
- Result: Showed UUID as fallback
Fix:
- workflowSerializer.js line 25: Added prompt_name to serialization
- Now saves both prompt_id AND prompt_name in graph_data
- On load: prompt_name is restored → AnalysisNode shows readable name
Testing:
- Create workflow with analysis node + prompt selection
- Save → Canvas should show "Pipeline: Körper-Analyse" (not UUID)
- Reload → Canvas should still show readable name (not UUID)
- AdminFocusAreasPage: Full CRUD for focus area definitions
- Route: /admin/focus-areas
- AdminPanel: Link zu Focus Areas (neben Goal Types)
- api.js: 7 neue Focus Area Endpoints
Features:
- Category-grouped display (7 categories)
- Inline editing
- Active/Inactive toggle
- Create form with validation
- Show/Hide inactive areas
Next: Goal Form Multi-Select
Implemented progress tracking system for all goals.
**Backend:**
- Migration 030: goal_progress_log table with unique constraint per day
- Trigger: Auto-update goal.current_value from latest progress
- Endpoints: GET/POST/DELETE /api/goals/{id}/progress
- Pydantic Models: GoalProgressCreate, GoalProgressUpdate
**Features:**
- Manual progress tracking for custom goals (flexibility, strength, etc.)
- Full history with date, value, note
- current_value always reflects latest progress entry
- One entry per day per goal (unique constraint)
- Cascade delete when goal is deleted
**API:**
- GET /api/goals/{goal_id}/progress - List all entries
- POST /api/goals/{goal_id}/progress - Log new progress
- DELETE /api/goals/{goal_id}/progress/{progress_id} - Delete entry
**Next:** Frontend UI (progress button, modal, history list)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
BREAKING: Replaces single 'primary goal' with weighted multi-goal system
Migration 027:
- New table: focus_areas (6 dimensions with percentages)
- Constraint: Sum must equal 100%
- Auto-migration: goal_mode → focus_areas for existing users
- Unique constraint: One active focus_areas per profile
Backend:
- get_focus_weights() V2: Reads from focus_areas table
- Fallback: Uses goal_mode if focus_areas not set
- New endpoints: GET/PUT /api/goals/focus-areas
- Validation: Sum=100, range 0-100
API:
- getFocusAreas() - Get current weights
- updateFocusAreas(data) - Update weights (upsert)
Focus dimensions:
1. weight_loss_pct (Fettabbau)
2. muscle_gain_pct (Muskelaufbau)
3. strength_pct (Kraftsteigerung)
4. endurance_pct (Ausdauer)
5. flexibility_pct (Beweglichkeit)
6. health_pct (Allgemeine Gesundheit)
Benefits:
- Multiple goals with custom priorities
- More flexible than single primary goal
- KI can use weighted scores
- Ready for Phase 0b placeholder integration
UI: Coming in next commit (slider interface)
Admin can now easily create custom goal types:
- New endpoint /api/goals/schema-info with table/column metadata
- 9 tables documented (weight, caliper, activity, nutrition, sleep, vitals, BP, rest_days, circumference)
- Table dropdown with descriptions (e.g., 'activity_log - Trainingseinheiten')
- Column dropdown dependent on selected table
- All columns documented in German with data types
- Fields optional (for complex calculation formulas)
UX improvements:
- No need to guess table/column names
- Clear descriptions for each field
- Type-safe selection (no typos)
- Cascading dropdowns (column depends on table)
Closes user feedback: 'Admin weiß nicht welche Tabellen/Spalten verfügbar sind'
BREAKING: Analysis page switched from old /insights/run to new /prompts/execute
Changes:
- Backend: Added save=true parameter to /prompts/execute
- When enabled, saves final output to ai_insights table
- Extracts content from pipeline output (last stage)
- Frontend api.js: Added save parameter to executeUnifiedPrompt()
- Frontend Analysis.jsx: Switched from api.runInsight() to api.executeUnifiedPrompt()
- Transforms new result format to match InsightCard expectations
- Pipeline outputs properly extracted and displayed
Fixes: PIPELINE_MASTER responses (old template being sent to AI)
The old /insights/run endpoint used raw template field, which for the
legacy "pipeline" prompt was literally "PIPELINE_MASTER". The new
executor properly handles stages and data processing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Backend: debug mode in prompt_executor with placeholder tracking
- Backend: show resolved/unresolved placeholders, final prompts, AI responses
- Frontend: test button in UnifiedPromptModal for saved prompts
- Frontend: debug output viewer with JSON preview
- Frontend: wider placeholder example fields in PlaceholderPicker
Resolves pipeline execution debugging issues.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
