- New placeholder: {{activity_detail}} returns formatted activity log
- Shows last 20 activities with date, type, duration, kcal, HR
- Makes activity analysis prompts work properly
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Placeholder resolver returns keys with {{ }} wrappers,
but resolve_placeholders expects clean keys.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Backend: integrate get_placeholder_example_values in execute_prompt_with_data
- Backend: now provides BOTH raw data AND processed placeholders
- Backend: unwrap Markdown-wrapped JSON (```json ... ```)
- Fixes old-style prompts that expect name, weight_trend, caliper_summary
Resolves unresolved placeholders issue.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Frontend: debug viewer now shows even when test fails
- Frontend: export button to download complete prompt config as JSON
- Backend: attach debug info to JSON validation errors
- Backend: include raw output and length in error details
Users can now debug failed prompts and export configs for analysis.
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>
Issue: template has NOT NULL constraint but pipeline-type prompts
don't use template (they use stages JSONB instead).
Solution: ALTER COLUMN template DROP NOT NULL before inserting
pipeline configs into ai_prompts.
Fixed Step 3 pipeline_configs migration:
- Simplified JSONB aggregation logic
- Properly scope pc alias in subqueries
- Use UNNEST with FROM clause for array expansion
Previous version had correlation issues with nested subqueries.
Migration 018:
- Add display_name column to ai_prompts
- Migrate existing prompts from hardcoded SLUG_LABELS
- Fallback: name if display_name is NULL
Backend:
- PromptCreate/Update models with display_name field
- create/update/duplicate endpoints handle display_name
- Fallback: use name if display_name not provided
Frontend:
- PromptEditModal: display_name input field
- Placeholder picker: button + dropdown with all placeholders
- Shows example values, inserts {{placeholder}} on click
- Analysis.jsx: use display_name instead of SLUG_LABELS
User-facing changes:
- Prompts now show custom display names (e.g. '🍽️ Ernährung')
- Admin can edit display names instead of hardcoded labels
- Template editor has 'Platzhalter einfügen' button
- No more hardcoded SLUG_LABELS in frontend
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend complete:
- Migration 017: Add category column to ai_prompts
- placeholder_resolver.py: 20+ placeholders with resolver functions
- Extended routers/prompts.py with CRUD endpoints:
* POST /api/prompts (create)
* PUT /api/prompts/:id (update)
* DELETE /api/prompts/:id (delete)
* POST /api/prompts/:id/duplicate
* PUT /api/prompts/reorder
* POST /api/prompts/preview
* GET /api/prompts/placeholders
* POST /api/prompts/generate (KI-assisted generation)
* POST /api/prompts/:id/optimize (KI analysis)
- Extended models.py with PromptCreate, PromptUpdate, PromptGenerateRequest
Frontend:
- AdminPromptsPage.jsx: Full CRUD UI with category filter, reordering
Meta-Features:
- KI generates prompts from goal description + example data
- KI analyzes and optimizes existing prompts
Next: PromptEditModal, PromptGenerator, api.js integration
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The frontend was sending quality_filter_level to the backend, but the
Pydantic ProfileUpdate model didn't include this field, so it was
silently ignored. Profile updates never actually saved the filter.
This is why the charts didn't react to filter changes - the backend
database was never updated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
Problem: Import failed with "invalid literal for int() with base 10: '37.95'"
because Apple Health exports HRV and other vitals with decimal values.
Root cause: Code used int() directly on string values with decimals.
Fix:
- Added safe_int(): parses decimals as float first, then rounds to int
- Added safe_float(): robust float parsing with error handling
- Applied to all vital value parsing: RHR, HRV, VO2 Max, SpO2, resp rate
Example: '37.95' → float(37.95) → int(38) ✓
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Errors during import were logged but not visible to user.
Changes:
- Backend: Collect error messages and return in response (first 10 errors)
- Frontend: Display error details in import result box
- UI: Red background when errors > 0, shows detailed error messages
Now users can see exactly which rows failed and why.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Import expected English column names, but German Apple Health/Omron
exports use German names with units.
Fixed:
- Apple Health: Support both English and German column names
- "Start" OR "Datum/Uhrzeit"
- "Resting Heart Rate" OR "Ruhepuls (count/min)"
- "Heart Rate Variability" OR "Herzfrequenzvariabilität (ms)"
- "VO2 Max" OR "VO2 max (ml/(kg·min))"
- "Oxygen Saturation" OR "Blutsauerstoffsättigung (%)"
- "Respiratory Rate" OR "Atemfrequenz (count/min)"
- Omron: Support column names with/without units
- "Systolisch (mmHg)" OR "Systolisch"
- "Diastolisch (mmHg)" OR "Diastolisch"
- "Puls (bpm)" OR "Puls"
- "Unregelmäßiger Herzschlag festgestellt" OR "Unregelmäßiger Herzschlag"
- "Mögliches AFib" OR "Vorhofflimmern"
Added debug logging for both imports to show detected columns.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Logs:
- CSV column names from first row
- Rows skipped due to missing date
- Rows skipped due to no vitals data
- Shows which fields were found/missing
Helps diagnose CSV format mismatches.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Import reported all entries as "updated" even when skipped
due to WHERE clause (source != 'manual')
Root cause: RETURNING returns NULL when WHERE clause prevents update,
but code counted NULL as "updated" instead of "skipped"
Fix:
- Check if result is None → skipped (WHERE prevented update)
- Check if xmax = 0 → inserted (new row)
- Otherwise → updated (existing row modified)
Affects:
- vitals_baseline.py: Apple Health import
- blood_pressure.py: Omron import
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
ModuleNotFoundError: No module named 'dateutil' beim Server-Start.
Ursache: vitals.py importiert dateutil.parser für Omron-Datumsformatierung,
aber python-dateutil fehlte in requirements.txt.
Fix: python-dateutil==2.9.0 zu requirements.txt hinzugefügt.
Nach dem Update: Docker Container neu bauen auf dem Pi:
cd /home/lars/docker/bodytrack-dev
docker compose -f docker-compose.dev-env.yml build --no-cache backend
docker compose -f docker-compose.dev-env.yml up -d
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>
- Import endpoints for Omron blood pressure CSV (German date format)
- Import endpoints for Apple Health vitals CSV
- Import UI tab in VitalsPage with drag & drop for both sources
- German month mapping for Omron date parsing ("13 März 2026")
- Upsert logic preserves manual entries (source != 'manual')
- Import result feedback (inserted/updated/skipped/errors)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Avg blood pressure (systolic/diastolic) 7d and 30d
- Latest VO2 Max value
- Avg SpO2 7d and 30d
- Backend now provides all metrics expected by frontend
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Migration 014:
- blood_pressure_systolic/diastolic (mmHg)
- pulse (bpm) - during BP measurement
- vo2_max (ml/kg/min) - from Apple Watch
- spo2 (%) - blood oxygen saturation
- respiratory_rate (breaths/min)
- irregular_heartbeat, possible_afib (boolean flags from Omron)
- Added 'omron' to source enum
Backend:
- Updated Pydantic models (VitalsEntry, VitalsUpdate)
- Updated all SELECT queries to include new fields
- Updated INSERT/UPDATE with COALESCE for partial updates
- Validation: at least one vital must be provided
Preparation for Omron + Apple Health imports
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend:
- New router: vitals.py with CRUD endpoints
- GET /api/vitals (list)
- GET /api/vitals/by-date/{date}
- POST /api/vitals (upsert)
- PUT /api/vitals/{id}
- DELETE /api/vitals/{id}
- GET /api/vitals/stats (7d/30d averages, trends)
- Registered in main.py
Frontend:
- VitalsPage.jsx with manual entry form
- List with inline editing
- Stats overview (averages, trend indicators)
- Added to CaptureHub (❤️ icon)
- Route /vitals in App.jsx
API:
- Added vitals methods to api.js
v9d Phase 2d - Vitals tracking complete
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- PostgreSQL returns numeric values as Decimal objects
- psycopg2.Json() cannot serialize Decimal to JSON
- Added convert_decimals() helper function
- Converts activity_data, context, and evaluation_result before saving
Fixes: Batch evaluation errors (31 errors 'Decimal is not JSON serializable')
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Shows first 10 errors with activity_id, training_type_id, and error message
- Helps debug evaluation failures
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Admin endpoints for profile configuration:
- Extended TrainingTypeCreate/Update models with profile field
- Added profile column to all SELECT queries
- Profile templates for Running, Meditation, Strength Training
- Template endpoints: list, get, apply
- Profile stats endpoint (configured/unconfigured count)
New file: profile_templates.py
- TEMPLATE_RUNNING: Endurance-focused with HR zones
- TEMPLATE_MEDITATION: Mental-focused (low HR ≤ instead of ≥)
- TEMPLATE_STRENGTH: Strength-focused
API Endpoints:
- GET /api/admin/training-types/profiles/templates
- GET /api/admin/training-types/profiles/templates/{key}
- POST /api/admin/training-types/{id}/profile/apply-template
- GET /api/admin/training-types/profiles/stats
Next: Frontend Admin-UI (ProfileEditor component)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
SQL Error: VALUES lists must all be the same length (line 130)
Cause: kcal_per_km row was missing validation_rules JSONB value
Fixed: Added validation_rules '{"min": 0, "max": 1000}'::jsonb
All 16 parameter rows now have correct 10 columns:
key, name_de, name_en, category, data_type, unit, source_field,
validation_rules, description_de, description_en
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Backend crashed on startup due to evaluation import failure
Solution: Wrap evaluation_helper import in try/except
Changes:
- Import evaluation_helper with error handling
- Add EVALUATION_AVAILABLE flag
- All evaluation calls now check flag before executing
- System remains functional even if evaluation system unavailable
This prevents backend crashes if:
- Migrations haven't run yet
- Dependencies are missing
- Import errors occur
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Automatic evaluation on activity INSERT/UPDATE:
- create_activity(): Evaluate after manual creation
- update_activity(): Re-evaluate after manual update
- import_activity_csv(): Evaluate after CSV import (INSERT + UPDATE)
- bulk_categorize_activities(): Evaluate after bulk training type assignment
All evaluation calls wrapped in try/except to prevent activity operations
from failing if evaluation encounters an error. Only activities with
training_type_id assigned are evaluated.
Phase 1.2 complete ✅
## Next Steps (Phase 2):
Admin-UI for training type profile configuration
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Creating new training types via Admin UI resulted in
'Internal Server Error' because abilities dict was passed directly
to PostgreSQL JSONB column without Json() wrapper.
Solution:
- Import Json from psycopg2.extras
- Wrap abilities_json with Json() in INSERT
- Wrap data.abilities with Json() in UPDATE
Same issue as rest_days JSONB fix (commit 7d627cf).
Closes#13
Problem: User can create multiple rest days of same type per date
(e.g., 2x Mental Rest on 2026-03-23) - makes no sense.
Solution: UNIQUE constraint on (profile_id, date, focus)
## Migration 012:
- Add focus column (extracted from rest_config JSONB)
- Populate from existing data
- Add NOT NULL constraint
- Add CHECK constraint (valid focus values)
- Add UNIQUE constraint (profile_id, date, focus)
- Add index for performance
## Backend:
- Insert focus column alongside rest_config
- Handle UniqueViolation gracefully
- User-friendly error: "Du hast bereits einen Ruhetag 'Muskelregeneration' für 23.03."
## Benefits:
- DB-level enforcement (clean)
- Fast queries (no JSONB scan)
- Clear error messages
- Prevents: 2x muscle_recovery same day
- Allows: muscle_recovery + mental_rest same day ✓
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Migration 011 removed UNIQUE constraint (profile_id, date) to allow
multiple rest days per date, but INSERT still used ON CONFLICT.
Error: psycopg2.errors.InvalidColumnReference: there is no unique or
exclusion constraint matching the ON CONFLICT specification
Solution: Remove ON CONFLICT clause, use plain INSERT.
Multiple entries per date now allowed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Error: psycopg2.ProgrammingError: can't adapt type 'dict'
Solution: Import psycopg2.extras.Json and wrap config_dict
Changes:
- Import Json from psycopg2.extras
- Wrap config_dict with Json() in INSERT
- Wrap config_dict with Json() in UPDATE
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Photos were always getting NULL date instead of form date,
causing frontend to fallback to created timestamp (today).
Root cause: FastAPI requires Form() wrapper for form fields when
mixing with File() parameters. Without it, the date parameter was
treated as query parameter and always received empty string.
Solution:
- Import Form from fastapi
- Change date parameter from str="" to str=Form("")
- Return photo_date instead of date in response (consistency)
Now photos correctly use the date from the upload form and can be
backdated when uploading later.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem:
- Photo upload with empty date parameter (date='')
- PostgreSQL rejects empty string for DATE field
- Error: "invalid input syntax for type date: ''"
- Occurred when saving circumference entry with only photo
Fix:
- Convert empty string to NULL before INSERT
- Check: date if date and date.strip() else None
- NULL is valid for optional date field
Test case:
- Circumference entry with only photo → should work now
- Photo without date → stored with date=NULL ✓
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Conceptual change: duration_minutes = actual sleep time (not time in bed)
Backend:
- Plausibility check: deep + rem + light = duration (awake separate)
- Import: duration = deep + rem + light (without awake)
- Updated error message: clarifies awake not counted
Frontend:
- Label: "Schlafdauer (reine Schlafzeit, Minuten)"
- Auto-calculate: bedtime-waketime minus awake_minutes
- Plausibility check: only validates sleep phases (not awake)
- Both NewEntry and Edit mode updated
Rationale:
- Standard in sleep tracking (Apple Health shows "Sleep", not "Time in Bed")
- Clearer semantics: duration = how long you slept
- awake_minutes tracked separately for analysis
- More intuitive for users
Example:
- Time in bed: 22:00 - 06:00 = 480 min (8h)
- Awake phases: 30 min
- Sleep duration: 450 min (7h 30min) ✓
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Segments crossing midnight were split into different nights
- 22:30-23:15 (21.03) → assigned to 21.03
- 00:30-02:45 (22.03) → assigned to 22.03
But both belong to the same night (21/22.03)!
Solution: Gap-based grouping
- Sort segments chronologically
- Group segments with gap < 2 hours
- Night date = wake_time.date() (last segment's end date)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend:
- New endpoint POST /api/sleep/import/apple-health
- Parses Apple Health sleep CSV format
- Maps German phase names (Kern→light, REM→rem, Tief→deep, Wach→awake)
- Aggregates segments by night (wake date)
- Stores raw segments in JSONB (sleep_segments)
- Does NOT overwrite manual entries (source='manual')
Frontend:
- Import button in SleepPage with file picker
- Progress indicator during import
- Success/error messages
- Auto-refresh after import
Documentation:
- Added architecture rules reference to CLAUDE.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Creates rest_days table for rest day tracking
- Creates vitals_log table for resting HR + HRV
- Creates weekly_goals table for training planning
- Extends profiles with hf_max and sleep_goal_minutes columns
- Extends activity_log with avg_hr and max_hr columns
- Fixes sleep_goal_minutes missing column error in stats endpoint
- Includes stats error handling in SleepWidget
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
PostgreSQL TIME type doesn't accept empty strings.
Converting empty bedtime/wake_time to None before INSERT/UPDATE.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Profile IDs are UUID type in the profiles table, not VARCHAR.
This was causing foreign key constraint error on migration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add sleep_log table with JSONB sleep_segments (Migration 009)
- Add sleep router with CRUD + stats endpoints (7d avg, 14d debt, trend, phases)
- Add SleepPage with quick/detail entry forms and inline edit
- Add SleepWidget to Dashboard showing last night + 7d average
- Add sleep navigation entry with Moon icon
- Register sleep router in main.py
- Add 9 new API methods in api.js
Phase 2b complete - ready for testing on dev
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Issue 1: Automatic training type mapping didn't work
- Root cause: Only English workout names were mapped
- Solution: Added 20+ German workout type mappings:
- "Traditionelles Krafttraining" → hypertrophy
- "Outdoor Spaziergang" → walk
- "Innenräume Spaziergang" → walk
- "Matrial Arts" → technique (handles typo)
- "Cardio Dance" → dance
- "Geist & Körper" → yoga
- Plus: Laufen, Gehen, Radfahren, Schwimmen, etc.
Issue 2: Reimporting CSV created duplicates without training types
- Root cause: Import always did INSERT with new UUID, no duplicate check
- Solution: Check if entry exists (profile_id + date + start_time)
- If exists: UPDATE with new data + training type mapping
- If new: INSERT as before
- Handles multiple workouts per day (different start times)
- "Skipped" count now includes updated entries
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend (v9d Phase 1b):
- Migration 006: Add abilities JSONB column + descriptions
- admin_training_types.py: Full CRUD endpoints for training types
- List, Get, Create, Update, Delete
- Abilities taxonomy endpoint (5 dimensions: koordinativ, konditionell, kognitiv, psychisch, taktisch)
- Validation: Cannot delete types in use
- Register admin_training_types router in main.py
Frontend:
- AdminTrainingTypesPage: Full CRUD UI
- Create/edit form with all fields (category, subcategory, names, icon, descriptions, sort_order)
- List grouped by category with color coding
- Delete with usage check
- Note about abilities mapping coming in v9f
- Add TrainingTypeDistribution to ActivityPage stats tab
- Add admin link in AdminPanel (v9d section)
- Update api.js with admin training types methods
Notes:
- Abilities mapping UI deferred to v9f (flexible prompt system)
- Placeholders (abilities column) in place for future AI analysis
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Migration 005: Add cardio subcategories (Gehen, Tanzen)
- Migration 005: Add new category "Geist & Meditation" with 4 subcategories
(Meditation, Atemarbeit, Achtsamkeit, Visualisierung)
- Update categories endpoint with mind category metadata
- Update Apple Health mapping: dance → dance, add meditation/mindfulness
- 6 new training types total
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add get_training_type_for_apple_health() mapping function (23 workout types)
- CSV import now automatically assigns training_type_id/category/subcategory
- New endpoint: GET /activity/uncategorized (grouped by activity_type)
- New endpoint: POST /activity/bulk-categorize (bulk update training types)
- New component: BulkCategorize with two-level dropdown selection
- ActivityPage: new "Kategorisieren" tab for existing activities
- Update CLAUDE.md: v9d Phase 1b progress
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 1: Training Types Basis
=============================
Backend:
- Migration 004: training_types table + seed data (24 types)
- New router: /api/training-types (grouped, flat, categories)
- Extend activity_log: training_type_id, training_category, training_subcategory
- Extend ActivityEntry model: support training type fields
Frontend:
- TrainingTypeSelect component (two-level dropdown)
- TrainingTypeDistribution component (pie chart)
- API functions: listTrainingTypes, listTrainingTypesFlat, getTrainingCategories
Quick Win: Logout Button
========================
- Add LogOut icon button in app header
- Confirm dialog before logout
- Redirect to / after logout
- Hover effect: red color on hover
Not yet integrated:
- TrainingTypeSelect not yet in ActivityPage form
- TrainingTypeDistribution not yet in Dashboard
(will be added in next commit)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1. Use window.location.href instead of navigate() for reliable redirect
2. Improve backend error message for already-used verification tokens
3. Show user-friendly message when token was already verified
4. Reduce redirect delay from 2s to 1.5s for better UX
Fixes:
- Empty page after email verification
- Generic error when clicking verification link twice
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend fixes:
- Fixed timezone-aware datetime comparison in verify_email endpoint
- Added trial_ends_at (14 days) for new registrations
- All datetime.now() calls now use timezone.utc
Frontend additions:
- Added EmailVerificationBanner component for unverified users
- Banner shows warning before trial banner in Dashboard
- Clear messaging about verification requirement
This fixes the 500 error on email verification and ensures new users
see both verification and trial status correctly.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Modified run_migrations() to only process files matching pattern: \d{3}_*.sql
This prevents utility scripts (check_features.sql) and manually applied
migrations (v9c_*.sql) from being executed.
Only properly numbered migrations like 003_add_email_verification.sql
will be processed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Added migration tracking and execution to db_init.py:
- Created schema_migrations table to track applied migrations
- Added run_migrations() to automatically apply pending SQL files
- Migrations from backend/migrations/*.sql are now applied on startup
This fixes the missing email verification columns (migration 003).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend:
- New endpoint: POST /api/auth/register
- New endpoint: GET /api/auth/verify/{token}
- Migration: Add email_verified, verification_token, verification_expires
- Helper: send_email() for reusable SMTP
- Validation: email format, password length (min 8), name
- Auto-login after verification (returns session token)
- Rate limit: 3 registrations per hour per IP
Features:
- Verification token valid for 24h
- Existing users marked as verified (grandfather clause)
- SMTP configured via .env (SMTP_HOST, SMTP_USER, SMTP_PASS)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Features:
- Manual entry form above data list
- Date picker with auto-load existing entries
- Upsert logic: creates new or updates existing entry
- Smart button text: "Hinzufügen" vs "Aktualisieren"
- Prevents duplicate entries per day
- Feature enforcement for nutrition_entries
Backend:
- POST /nutrition - Create or update entry (upsert)
- GET /nutrition/by-date/{date} - Load entry by date
- Auto-detects existing entry and switches to UPDATE mode
- Increments usage counter only on INSERT
Frontend:
- EntryForm component with date picker + macros inputs
- Auto-loads data when date changes
- Shows info message when entry exists
- Success/error feedback
- Disabled state while loading/saving
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Features:
- Import history panel showing all CSV imports with date, count, and range
- Edit/delete functionality for nutrition entries (inline editing)
- New backend endpoints: GET /import-history, PUT /{id}, DELETE /{id}
UI Changes:
- Import history displayed under import panel
- "Daten" tab now has edit/delete buttons per entry
- Inline form for editing macros (kcal, protein, fat, carbs)
- Confirmation dialog for deletion
Backend:
- nutrition.py: Added import_history, update_nutrition, delete_nutrition endpoints
- Groups imports by created date to show history
Frontend:
- NutritionPage: New DataTab and ImportHistory components
- api.js: Added nutritionImportHistory, updateNutrition, deleteNutrition
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem:
- /api/nutrition/weekly crashed with 500 Internal Server Error
- TypeError: strptime() argument 1 must be str, not datetime.date
Root Cause:
- d['date'] from PostgreSQL is already datetime.date object
- datetime.strptime() expects string input
- Line 156: wk=datetime.strptime(d['date'],'%Y-%m-%d').strftime('%Y-W%V')
Solution:
- Added type check before strptime()
- If date already has strftime method → use directly
- Else → parse as string first
- Works with both datetime.date objects and strings
Tested:
- /nutrition page loads without error
- Weekly aggregation works correctly
- Chart displays nutrition data
Closes: BUG-001
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Behebt IndentationError in Zeile 204 der _check_impl() Funktion.
Die Funktion wurde beim Connection-Pool-Fix erstellt, hatte aber
inkonsistente Einrückungen (8 statt 4 Spaces nach der ersten Zeile).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add user-facing usage overview endpoint
- Returns all features with usage, limits, reset info
- Fully dynamic - automatically includes new features
- Phase 3: Frontend Display preparation
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>
Critical bug: usage limits were never resetting after first month because
reset_at timestamp was not updated during ON CONFLICT UPDATE.
This caused users to stay permanently blocked after reaching monthly limit once.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Critical fixes for feature enforcement:
- Add GET /api/features/{feature_id}/check-access endpoint (was missing!)
- Add migration for missing features: data_export, csv_import
- These features were used in frontend but didn't exist in DB
This fixes:
- "No analysis available" when setting KI limit
- Export features not working
- Frontend calling non-existent API endpoint
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove active=true filter - admins need to configure all tiers
- Add reset_period to features query for frontend display
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
New router: routers/coupons.py
Admin endpoints:
- GET /api/coupons - List all coupons with stats
- POST /api/coupons - Create new coupon
- PUT /api/coupons/{id} - Update coupon
- DELETE /api/coupons/{id} - Soft-delete (set active=false)
- GET /api/coupons/{id}/redemptions - Redemption history
User endpoints:
- POST /api/coupons/redeem - Redeem coupon code
Features:
- Three coupon types: single_use, period, wellpass
- Wellpass logic: Pauses existing personal grants, resumes after expiry
- Max redemptions limit (NULL = unlimited)
- Validity period checks
- Activity logging
- Duplicate redemption prevention
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
New router: routers/subscription.py
Endpoints:
- GET /api/subscription/me - Own subscription info (tier, trial, grants)
- GET /api/subscription/usage - Feature usage with limits
- GET /api/subscription/limits - All feature limits for current tier
Features:
- Shows effective tier (considers access_grants)
- Lists active access grants (from coupons, trials)
- Per-feature usage tracking
- Email verification status
Uses new middleware: get_effective_tier(), check_feature_access()
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Changed all profile_id columns from TEXT to UUID to match profiles.id type.
Changed all auto-generated IDs from gen_random_uuid() to uuid_generate_v4()
to match existing schema.sql convention.
Fixed tables:
- tier_limits: id TEXT → UUID
- user_feature_restrictions: id, profile_id, created_by TEXT → UUID
- user_feature_usage: id, profile_id TEXT → UUID
- coupons: id, created_by TEXT → UUID
- coupon_redemptions: id, coupon_id, profile_id, access_grant_id TEXT → UUID
- access_grants: id, profile_id, coupon_id, paused_by TEXT → UUID
- user_activity_log: id, profile_id TEXT → UUID
- user_stats: profile_id TEXT → UUID
- profiles.invited_by: TEXT → UUID
This fixes: foreign key constraint "user_feature_restrictions_profile_id_fkey"
cannot be implemented - Key columns "profile_id" and "id" are of
incompatible types: text and uuid
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
PROBLEM:
- Backend crasht beim Start auf Prod
- Migration schlägt fehl: column 'meas_id' does not exist
- SQLite ai_insights hat Legacy-Spalte meas_id
- PostgreSQL schema hat diese Spalte nicht mehr
FIX:
- COLUMN_WHITELIST für ai_insights hinzugefügt
- Nur erlaubte Spalten werden migriert:
id, profile_id, scope, content, created
- meas_id wird beim Import gefiltert
DATEIEN:
- backend/migrate_to_postgres.py
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
