Implemented global quality_filter_level in user profiles for consistent
data filtering across all views (Dashboard, History, Charts, KI-Pipeline).
Backend changes:
- Migration 016: Add quality_filter_level column to profiles table
- quality_filter.py: Centralized helper functions for SQL filtering
- insights.py: Apply global filter in _get_profile_data()
- activity.py: Apply global filter in list_activity()
Frontend changes:
- SettingsPage.jsx: Add Datenqualität section with 4-level selector
- History.jsx: Use global quality filter from profile context
Filter levels: all, quality (good+excellent+acceptable), very_good
(good+excellent), excellent (only excellent)
Closes#31
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Notiert an 3 Stellen:
1. insights.py: TODO-Kommentar im Code
2. ROADMAP.md: Deliverable bei M0.2 (lokal, nicht im Git)
3. Gitea Issue #28: Kommentar mit Spezifikation
Zukünftig:
- GET /api/insights/run/{slug}?quality_level=quality
- 4 Stufen: all, quality, very_good, excellent
- Frontend: Dropdown wie in History.jsx
- Pipeline-Configs können Standard-Level haben
User-Request: Quality-Level-Auswahl für KI-Analysen
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
**Backend (insights.py):**
- Extended _get_profile_data() to fetch sleep, rest_days, vitals
- Added template variables for Sleep Module:
{{sleep_summary}}, {{sleep_detail}}, {{sleep_avg_duration}}, {{sleep_avg_quality}}
- Added template variables for Rest Days:
{{rest_days_summary}}, {{rest_days_count}}, {{rest_days_types}}
- Added template variables for Vitals:
{{vitals_summary}}, {{vitals_detail}}, {{vitals_avg_hr}}, {{vitals_avg_hrv}},
{{vitals_avg_bp}}, {{vitals_vo2_max}}
**Frontend (Analysis.jsx):**
- Added 12 new template variables to VARS list in PromptEditor
- Enables AI prompt creation for Sleep, Rest Days, and Vitals analysis
All modules now have AI evaluation support for future prompt creation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Create feature_logger.py with JSON logging infrastructure
- Add log_feature_usage() calls to all 9 routers after check_feature_access()
- Logs written to /app/logs/feature-usage.log
- Tracks all usage (not just violations) for future analysis
- Phase 2: Non-blocking monitoring complete
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Fixes two critical bugs in AI analysis storage:
1. History now works - analyses are saved, not overwritten
- Removed DELETE statements before INSERT in insights.py
- All analyses are now preserved per scope
- Displayed in descending order by creation date
2. Pipeline saves under correct scope 'pipeline' instead of 'gesamt'
- Changed scope from 'gesamt' to 'pipeline' in pipeline endpoint
- Pipeline results now appear under correct category in history
3. Fixed pipeline appearing twice in UI
- Filter now excludes both 'pipeline_*' and 'pipeline' from individual list
- Pipeline only appears in dedicated section at top
Changes:
- backend/routers/insights.py: Removed DELETE, changed scope to 'pipeline'
- frontend/src/pages/Analysis.jsx: Fixed filter to exclude 'pipeline'
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Reverts all feature enforcement changes (commits 3745ebd, cbad50a, cd4d912, 8415509)
to restore original working functionality.
Issues caused by feature enforcement implementation:
- Export buttons disappeared and never reappeared
- KI analysis counter not incrementing
- New analyses not saving
- Pipeline appearing twice
- Many core features broken
Restored files to working state before enforcement implementation (commit 0210844):
- Backend: auth.py, insights.py, exportdata.py, importdata.py, nutrition.py, activity.py
- Frontend: Analysis.jsx, SettingsPage.jsx, api.js
- Removed: FeatureGate.jsx, useFeatureAccess.js
The original simple AI limit system (ai_enabled, ai_limit_day) is now active again.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
