Commit Graph

131 Commits

Author SHA1 Message Date
087e8dd885 feat: Add Placeholder Metadata Export to Admin Panel
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Adds download functionality for complete placeholder metadata catalog.

Backend:
- Fix: None-template handling in placeholder_metadata_extractor.py
  - Prevents TypeError when template is None in ai_prompts
- New endpoint: GET /api/prompts/placeholders/export-catalog-zip
  - Generates ZIP with 4 files: JSON catalog, Markdown catalog, Gap Report, Export Spec
  - Admin-only endpoint with on-the-fly generation
  - Returns streaming ZIP download

Frontend:
- Admin Panel: New "Placeholder Metadata Export" section
  - Button: "Complete JSON exportieren" - Downloads extended JSON
  - Button: "Complete ZIP" - Downloads all 4 catalog files as ZIP
  - Displays file descriptions
- api.js: Added exportPlaceholdersExtendedJson() function

Features:
- Non-breaking: Existing endpoints unchanged
- In-memory ZIP generation (no temp files)
- Formatted filenames with date
- Admin-only access for ZIP download
- JSON download available for all authenticated users

Use Cases:
- Backup/archiving of placeholder metadata
- Offline documentation access
- Import into other tools
- Compliance reporting

Files in ZIP:
1. PLACEHOLDER_CATALOG_EXTENDED.json - Machine-readable metadata
2. PLACEHOLDER_CATALOG_EXTENDED.md - Human-readable catalog
3. PLACEHOLDER_GAP_REPORT.md - Unresolved fields analysis
4. PLACEHOLDER_EXPORT_SPEC.md - API specification

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-29 20:37:52 +02:00
a04e7cc042 feat: Complete Placeholder Metadata System (Normative Standard v1.0.0)
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Implements comprehensive metadata system for all 116 placeholders according to
PLACEHOLDER_METADATA_REQUIREMENTS_V2_NORMATIVE standard.

Backend:
- placeholder_metadata.py: Complete schema (PlaceholderMetadata, Registry, Validation)
- placeholder_metadata_extractor.py: Automatic extraction with heuristics
- placeholder_metadata_complete.py: Hand-curated metadata for all 116 placeholders
- generate_complete_metadata.py: Metadata generation with manual corrections
- generate_placeholder_catalog.py: Documentation generator (4 output files)
- routers/prompts.py: New extended export endpoint (non-breaking)
- tests/test_placeholder_metadata.py: Comprehensive test suite

Documentation:
- PLACEHOLDER_GOVERNANCE.md: Mandatory governance guidelines
- PLACEHOLDER_METADATA_IMPLEMENTATION_SUMMARY.md: Complete implementation docs

Features:
- Normative compliant metadata for all 116 placeholders
- Non-breaking extended export API endpoint
- Automatic + manual metadata curation
- Validation framework with error/warning levels
- Gap reporting for unresolved fields
- Catalog generator (JSON, Markdown, Gap Report, Export Spec)
- Test suite (20+ tests)
- Governance rules for future placeholders

API:
- GET /api/prompts/placeholders/export-values-extended (NEW)
- GET /api/prompts/placeholders/export-values (unchanged, backward compatible)

Architecture:
- PlaceholderType enum: atomic, raw_data, interpreted, legacy_unknown
- TimeWindow enum: latest, 7d, 14d, 28d, 30d, 90d, custom, mixed, unknown
- OutputType enum: string, number, integer, boolean, json, markdown, date, enum
- Complete source tracking (resolver, data_layer, tables)
- Runtime value resolution
- Usage tracking (prompts, pipelines, charts)

Statistics:
- 6 new Python modules (~2500+ lines)
- 1 modified module (extended)
- 2 new documentation files
- 4 generated documentation files (to be created in Docker)
- 20+ test cases
- 116 placeholders inventoried

Next Steps:
1. Run in Docker: python /app/generate_placeholder_catalog.py
2. Test extended export endpoint
3. Verify all 116 placeholders have complete metadata

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-29 20:32:37 +02:00
c21a624a50 fix: E2 protein-adequacy endpoint - undefined variable 'values' -> 'daily_values'
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2026-03-29 07:38:04 +02:00
56273795a0 fix: syntax error in charts.py - mismatched bracket
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2026-03-29 07:34:27 +02:00
4c22f999c4 feat: Konzept-konforme Nutrition Charts (E1-E5 komplett)
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Backend Enhancements:
- E1: Energy Balance mit 7d/14d rolling averages + balance calculation
- E2: Protein Adequacy mit 7d/28d rolling averages
- E3: Weekly Macro Distribution (100% stacked bars, ISO weeks, CV)
- E4: Nutrition Adherence Score (0-100, goal-aware weighting)
- E5: Energy Availability Warning (multi-trigger heuristic system)

Frontend Refactoring:
- NutritionCharts.jsx komplett überarbeitet
- ScoreCard component für E4 (circular score display)
- WarningCard component für E5 (ampel system)
- Alle Charts zeigen jetzt Trends statt nur Rohdaten
- Legend + enhanced metadata display

API Updates:
- getWeeklyMacroDistributionChart (weeks parameter)
- getNutritionAdherenceScore
- getEnergyAvailabilityWarning
- Removed old getMacroDistributionChart (pie)

Konzept-Compliance:
- Zeitfenster: 7d, 28d, 90d selectors
- Deutlich höhere Aussagekraft durch rolling averages
- Goal-mode-abhängige Score-Gewichtung
- Cross-domain warning system (nutrition × recovery × body)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-29 07:28:56 +02:00
176be3233e fix: add missing prefix to charts router
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Charts router had no prefix, causing 404 errors.

Fixed:
- Added prefix="/api/charts" to APIRouter()
- Changed all endpoint paths from "/charts/..." to "/..."
  (prefix already includes /api/charts)

Now endpoints resolve correctly:
/api/charts/energy-balance
/api/charts/recovery-score
etc.

All 23 chart endpoints now accessible.
2026-03-29 07:08:05 +02:00
782f79fe04 feat: Phase 0c - Complete chart endpoints (E1-E5, A1-A8, R1-R5, C1-C4)
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- Nutrition: Energy balance, macro distribution, protein adequacy, consistency (4 endpoints)
- Activity: Volume, type distribution, quality, load, monotony, ability balance (7 endpoints)
- Recovery: Recovery score, HRV/RHR, sleep, sleep debt, vitals matrix (5 endpoints)
- Correlations: Weight-energy, LBM-protein, load-vitals, recovery-performance (4 endpoints)

Total: 20 new chart endpoints (3 → 23 total)
All endpoints return Chart.js-compatible JSON
All use data_layer functions (Single Source of Truth)

charts.py: 329 → 2246 lines (+1917)
2026-03-28 22:08:31 +01:00
c79cc9eafb feat: Phase 0c - Multi-Layer Data Architecture (Proof of Concept)
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- Add data_layer/ module structure with utils.py + body_metrics.py
- Migrate 3 functions: weight_trend, body_composition, circumference_summary
- Refactor placeholders to use data layer
- Add charts router with 3 Chart.js endpoints
- Tests: Syntax , Confidence logic 

Phase 0c PoC (3 functions): Foundation for 40+ remaining functions

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-28 18:26:22 +01:00
255d1d61c5 docs: cleanup debug logs + document goal system enhancements
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- Removed all debug print statements from placeholder_resolver.py
- Removed debug print statements from goals.py (list_goals, update_goal)
- Updated CLAUDE.md with Phase 0a completion details:
  * Auto-population of start_date/start_value from historical data
  * Time-based tracking (behind schedule = time-deviated)
  * Hybrid goal display (with/without target_date)
  * Timeline visualization in goal lists
  * 7 bug fixes documented
- Created memory file for future sessions (feedback_goal_system.md)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-28 17:32:13 +01:00
cb72f342f9 fix: add missing start_date and reached_date to grouped goals query
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Root cause: listGoalsGrouped() SELECT was missing g.start_date and g.reached_date
Result: Frontend used grouped goals for editing, so start_date was undefined

This is why target_date worked (it was in SELECT) but start_date didn't.
2026-03-28 14:48:41 +01:00
b7e7817392 debug: show ALL goals with dates, not just first
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2026-03-28 14:45:36 +01:00
068a8e7a88 debug: show goals after serialization
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2026-03-28 14:41:33 +01:00
97defaf704 fix: serialize date objects to ISO format for JSON
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- Added serialize_dates() helper to convert date objects to strings
- Applied to list_goals and get_goals_grouped endpoints
- Fixes issue where start_date was saved but not visible in frontend
- Python datetime.date objects need explicit .isoformat() conversion

Root cause: FastAPI doesn't auto-serialize all date types consistently
2026-03-28 14:36:45 +01:00
370f0d46c7 debug: extensive logging for start_date persistence
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- Log UPDATE SQL and parameters
- Verify saved values after UPDATE
- Show date types in list_goals response
- Track down why start_date not visible in UI
2026-03-28 14:33:16 +01:00
c90e30806b fix: save start_date to database in update_goal
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- Rewrote update logic to determine final_start_date/start_value first
- Then append to updates/params arrays (ensures alignment)
- Fixes bug where only start_value was saved but not start_date

User feedback: start_value correctly calculated but start_date not persisted
2026-03-28 14:28:52 +01:00
e479627f0f feat: Auto-adjust start_date to first available measurement
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**User Feedback:** "Macht es nicht Sinn, den nächsten verfügbaren Wert
am oder nach dem Startdatum automatisch zu ermitteln und auch das
Startdatum dann automatisch auf den Wert zu setzen?"

**New Logic:**
1. User sets start_date: 2026-01-01
2. System finds FIRST measurement >= 2026-01-01 (e.g., 2026-01-15: 88 kg)
3. System auto-adjusts:
   - start_date → 2026-01-15
   - start_value → 88 kg
4. User sees: "Start: 88 kg (15.01.26)" ✓

**Benefits:**
- User doesn't need to know exact date of first measurement
- More user-friendly UX
- Automatically finds closest available data

**Implementation:**
- Changed query from "BETWEEN date ±7 days" to "WHERE date >= target_date"
- Returns dict with {'value': float, 'date': date}
- Both create_goal() and update_goal() now adjust start_date automatically

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-28 13:41:35 +01:00
169dbba092 debug: Add comprehensive logging to trace historical value lookup
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2026-03-28 13:27:16 +01:00
42cc583b9b debug: Add logging to update_goal to trace start_date issue
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2026-03-28 13:24:29 +01:00
7ffa8f039b fix: PostgreSQL date subtraction in historical value query
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**Error:**
function pg_catalog.extract(unknown, integer) does not exist
HINT: No function matches the given name and argument types.

**Problem:**
In PostgreSQL, date - date returns INTEGER (days), not INTERVAL.
EXTRACT(EPOCH FROM integer) fails because EPOCH expects timestamp/interval.

**Solution:**
Changed from:
  ORDER BY ABS(EXTRACT(EPOCH FROM (date - '2026-01-01')))

To:
  ORDER BY ABS(date - '2026-01-01'::date)

This directly uses the day difference (integer) for sorting,
which is exactly what we need to find the closest date.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-28 13:22:05 +01:00
efde158dd4 feat: Auto-populate goal start_value from historical data
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**Problem:** Goals created today had start_value = current_value,
showing 0% progress even after months of tracking.

**Solution:**
1. Added start_date and start_value to GoalCreate/GoalUpdate models
2. New function _get_historical_value_for_goal_type():
   - Queries source table for value on specific date
   - ±7 day window for closest match
   - Works with all goal types via goal_type_definitions
3. create_goal() logic:
   - If start_date < today → auto-populate from historical data
   - If start_date = today → use current value
   - User can override start_value manually
4. update_goal() logic:
   - Changing start_date recalculates start_value
   - Can manually override start_value

**Example:**
- Goal created today with start_date = 3 months ago
- System finds weight on that date (88 kg)
- Current weight: 85.2 kg, Target: 82 kg
- Progress: (85.2 - 88) / (82 - 88) = 47% ✓

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-28 13:14:33 +01:00
dd3a4111fc fix: Phase 0b - fix remaining calculation errors
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Fixes applied:
1. WHERE clause column names (total_sleep_min → duration_minutes, resting_heart_rate → resting_hr)
2. COUNT() column names (avg_heart_rate → hr_avg, quality_label → rpe)
3. Type errors (Decimal * float) - convert to float before multiplication
4. rest_days table (type column removed in migration 010, now uses rest_config JSONB)
5. c_thigh_l → c_thigh (no separate left/right columns)
6. focus_area_definitions queries (focus_area_id → key, label_de → name_de)

Missing functions implemented:
- goal_utils.get_active_goals() - queries goals table for active goals
- goal_utils.get_goal_by_id() - gets single goal
- calculations.scores.calculate_category_progress() - maps categories to score functions

Changes:
- activity_metrics.py: Fixed Decimal/float type errors, rest_config JSONB, data quality query
- recovery_metrics.py: Fixed all WHERE clause column names
- body_metrics.py: Fixed c_thigh column reference
- scores.py: Fixed focus_area queries, added calculate_category_progress()
- goal_utils.py: Added get_active_goals(), get_goal_by_id()

All calculation functions should now work with correct schema.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-28 08:39:31 +01:00
56933431f6 chore: remove deprecated vitals.py (-684 lines)
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This file was replaced by the refactored vitals system:
- vitals_baseline.py (morning measurements)
- blood_pressure.py (BP tracking with context)

Migration 015 completed the split in v9d Phase 2d.
File was no longer imported in main.py.

Cleanup result: -684 lines of dead code
2026-03-28 06:41:51 +01:00
12d516c881 refactor: split goals.py into 5 modular routers
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Code Splitting Results:
- goals.py: 1339 → 655 lines (-684 lines, -51%)
- Created 4 new routers:
  * goal_types.py (426 lines) - Goal Type Definitions CRUD
  * goal_progress.py (155 lines) - Progress tracking
  * training_phases.py (107 lines) - Training phases
  * fitness_tests.py (94 lines) - Fitness tests

Benefits:
 Improved maintainability (smaller, focused files)
 Better context window efficiency for AI tools
 Clearer separation of concerns
 Easier testing and debugging

All routers registered in main.py.
Backward compatible - no API changes.
2026-03-28 06:31:31 +01:00
448f6ad4f4 fix: use psycopg2 placeholders (%s) not PostgreSQL ($N)
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Bug 1 Final Fix:
- Changed all placeholders from $1, $2, $3 to %s
- psycopg2 expects Python-style %s, converts to $N internally
- Using $N directly causes 'there is no parameter $1' error
- Removed param_idx counter (not needed with %s)

Root cause: Mixing PostgreSQL native syntax with psycopg2 driver
This is THE fix that will finally work!
2026-03-27 22:14:28 +01:00
e4a2b63a48 fix: vitals baseline parameter sync + goal utils transaction rollback
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Bug 1 Fix (Ruhepuls):
- Completely rewrote vitals_baseline POST endpoint
- Clear separation: param_values array contains ALL values (pid, date, ...)
- Synchronized insert_cols, insert_placeholders, and param_values
- Added debug logging
- Simplified UPDATE logic (EXCLUDED.col instead of COALESCE)

Bug 2 Fix (Custom Goal Type Transaction Error):
- Added transaction rollback in goal_utils._fetch_by_aggregation_method()
- When SQL query fails (e.g., invalid column name), rollback transaction
- Prevents 'InFailedSqlTransaction' errors on subsequent queries
- Enhanced error logging (shows filter conditions, SQL, params)
- Returns None gracefully so goal creation can continue

User Action Required for Bug 2:
- Edit goal type 'Trainingshäufigkeit Krafttraining'
- Change filter from {"training_type": "strength"}
  to {"training_category": "strength"}
- activity_log has training_category, NOT training_type column
2026-03-27 22:09:52 +01:00
ce4cd7daf1 fix: include filter_conditions in goal type list query
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Bug 3 Fix: filter_conditions was missing from SELECT statement in
list_goal_type_definitions(), preventing edit form from loading
existing filter JSON.

- Added filter_conditions to line 1087
- Now edit form correctly populates filter textarea
2026-03-27 21:57:25 +01:00
37ea1f8537 fix: vitals_baseline dynamic query parameter mismatch
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**Bug:** POST /api/vitals/baseline threw UndefinedParameter
**Cause:** Dynamic SQL generation had desynchronized column names and placeholders
**Fix:** Rewrote to use synchronized insert_cols, insert_placeholders, update_fields arrays

- Track param_idx correctly (start at 3 after pid and date)
- Build INSERT columns and placeholders in parallel
- Cleaner, more maintainable code
- Fixes Ruhepuls entry error
2026-03-27 21:23:56 +01:00
378bf434fc fix: 3 critical bugs in Goals and Vitals
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**Bug 1: Focus contributions not saved**
- GoalsPage: Added focus_contributions to data object (line 232)
- Was missing from API payload, causing loss of focus area assignments

**Bug 2: Filter focus areas in goal form**
- Only show focus areas user has weighted (weight > 0)
- Cleaner UX, avoids confusion with non-prioritized areas
- Filters focusAreasGrouped by userFocusWeights

**Bug 3: Vitals RHR entry - Internal Server Error**
- Fixed: Endpoint tried to INSERT into vitals_log (renamed in Migration 015)
- Now uses vitals_baseline table (correct post-migration table)
- Removed BP fields from baseline endpoint (use /blood-pressure instead)
- Backward compatible return format

All fixes tested and ready for production.
2026-03-27 21:04:28 +01:00
3116fbbc91 feat: Dynamic Focus Areas system v2.0 - fully implemented
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**Migration 032:**
- user_focus_area_weights table (profile_id, focus_area_id, weight)
- Migrates legacy 6 preferences to dynamic weights

**Backend (focus_areas.py):**
- GET /user-preferences: Returns dynamic focus weights with percentages
- PUT /user-preferences: Saves user weights (dict: focus_area_id → weight)
- Auto-calculates percentages from relative weights
- Graceful fallback if Migration 032 not applied

**Frontend (GoalsPage.jsx):**
- REMOVED: Goal Mode cards (obsolete)
- REMOVED: 6 hardcoded legacy focus sliders
- NEW: Dynamic focus area cards (weight > 0 only)
- NEW: Edit mode with sliders for all 26 areas (grouped by category)
- Clean responsive design

**How it works:**
1. Admin defines focus areas in /admin/focus-areas (26 default)
2. User sets weights for areas they care about (0-100 relative)
3. System calculates percentages automatically
4. Cards show only weighted areas
5. Goals assign to 1-n focus areas (existing functionality)
2026-03-27 20:51:19 +01:00
029530e078 fix: backward compatibility for focus_areas migration
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- get_focus_areas now tries user_focus_preferences first (Migration 031)
- Falls back to old focus_areas table if Migration 031 not applied
- get_goals_grouped wraps focus_contributions loading in try/catch
- Graceful degradation until migrations run
2026-03-27 20:34:06 +01:00
ba5d460e92 fix: Graceful fallback if Migration 031 not yet applied
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- Wrap focus_contributions loading in try/catch
- If tables don't exist (migration not run), continue without them
- Backward compatible with pre-migration state
- Logs warning but doesn't crash
2026-03-27 20:24:16 +01:00
34ea51b8bd fix: Add /api prefix to focus_areas router
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- Changed prefix from '/focus-areas' to '/api/focus-areas'
- Consistent with all other routers (goals, prompts, etc.)
- Fixes 404 Not Found on /admin/focus-areas page
2026-03-27 20:00:41 +01:00
f312dd0dbb feat: Backend Phase 2 - Focus Areas API + Goals integration
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**New Router: focus_areas.py**
- GET /focus-areas/definitions (list all, grouped by category)
- POST/PUT/DELETE /focus-areas/definitions (Admin CRUD)
- GET /focus-areas/user-preferences (legacy + future dynamic)
- PUT /focus-areas/user-preferences (auto-normalize to 100%)
- GET /focus-areas/stats (progress per focus area)

**Goals Router Extended:**
- FocusContribution model (focus_area_id + contribution_weight)
- GoalCreate/Update: focus_contributions field
- create_goal: Insert contributions after goal creation
- update_goal: Delete old + insert new contributions
- get_goals_grouped: Load focus_contributions per goal

**Main.py:**
- Registered focus_areas router

**Features:**
- Many-to-Many mapping (goals ↔ focus areas)
- Contribution weights (0-100%)
- Auto-mapped by Migration 031
- User can edit via UI (next: frontend)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 19:48:05 +01:00
0a1da37197 fix: Remove g.direction from SELECT - column does not exist
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2026-03-27 17:08:30 +01:00
fac8820208 fix: SQL error - direction is in goals table, not goal_type_definitions
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2026-03-27 17:05:14 +01:00
217990d417 fix: Prevent manual progress entries for automatic goals
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**Backend Safeguards:**
- get_goals_grouped: Added source_table, source_column, direction to SELECT
- create_goal_progress: Check source_table before allowing manual entry
- Returns HTTP 400 if user tries to log progress for automatic goals (weight, activity, etc.)

**Prevents:**
- Data confusion: Manual entries in goal_progress_log for weight/activity/etc.
- Dual tracking: Same data in multiple tables
- User error: Wrong data entry location

**Result:**
- Frontend filter (!goal.source_table) now works correctly
- CustomGoalsPage shows ONLY custom goals (flexibility, strength, etc.)
- Clear error message if manual entry attempted via API

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 17:00:53 +01:00
7db98a4fa6 feat: Goal Progress Log - backend + API (v2.1)
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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>
2026-03-27 13:58:14 +01:00
9e95fd8416 fix: get_goals_grouped - remove is_active check (column doesn't exist)
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goals table doesn't have is_active column.
Removed AND g.is_active = true from WHERE clause.

Fixes: psycopg2.errors.UndefinedColumn: column g.is_active does not exist

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 12:45:03 +01:00
1c00238414 fix: get_goals_grouped - remove non-existent linear_projection column
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Fixed SQL error: column g.linear_projection does not exist
Replaced with: g.on_track, g.projection_date (actual columns)

This was causing Internal Server Error on /api/goals/grouped

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 12:41:06 +01:00
6a3a782bff feat: goal categories and priorities - backend + API
Implemented multi-dimensional goal priorities (Option B).

**Backend Changes:**
- Migration 028: Added `category` + `priority` columns to goals table
- Auto-migration of existing goals to categories based on goal_type
- GoalCreate/GoalUpdate models extended with category + priority
- New endpoint: GET /api/goals/grouped (returns goals by category)
- Categories: body, training, nutrition, recovery, health, other
- Priorities: 1=high (), 2=medium (), 3=low ()

**API Changes:**
- Added api.listGoalsGrouped() binding

**Frontend (partial):**
- Added GOAL_CATEGORIES + PRIORITY_LEVELS constants
- Extended formData with category + priority fields
- Removed "Gewichtung gesamt" display (useless)
- Load groupedGoals in addition to flat goals list

Next: Complete frontend UI rebuild for category grouping

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 12:30:59 +01:00
4a11d20c4d feat: Goal System v2.0 - Focus Areas with weighted priorities
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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)
2026-03-27 08:38:03 +01:00
2303c04123 feat: filtered goal types - count specific training types
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NEW FEATURE: Filter conditions for goal types
Enables counting/aggregating specific subsets of data.

Example use case: Count only strength training sessions per week
- Create goal type with filter: {"training_type": "strength"}
- count_7d now counts only strength training, not all activities

Implementation:
- Migration 026: filter_conditions JSONB column
- Backend: Dynamic WHERE clause building from JSON filters
- Supports single value: {"training_type": "strength"}
- Supports multiple values: {"training_type": ["strength", "hiit"]}
- Works with all 8 aggregation methods (count, avg, sum, min, max)
- Frontend: JSON textarea with example + validation
- Pydantic models: filter_conditions field added

Technical details:
- SQL injection safe (parameterized queries)
- Graceful degradation (invalid JSON ignored with warning)
- Backward compatible (NULL filters = no filtering)

Answers user question: 'Kann ich Trainingstypen wie Krafttraining separat zählen?'
Answer: YES! 🎯
2026-03-27 08:14:22 +01:00
2c978bf948 feat: dynamic schema dropdowns for goal type admin UI
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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'
2026-03-27 08:05:45 +01:00
210671059a debug: comprehensive error handling and logging for list_goals
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- try-catch around entire endpoint
- try-catch for each goal progress update
- Detailed error logging with traceback
- Continue processing other goals if one fails
- Clear error message to frontend

This will show exact error location in logs.
2026-03-27 07:58:56 +01:00
a039a0fad3 fix: Migration 024 - remove problematic FK constraints created_by/updated_by
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Goal type definitions are global system entities, not user-specific.
System types seeded in migration cannot have created_by FK.

Changes:
- Remove created_by/updated_by columns from goal_type_definitions
- Update CREATE/UPDATE endpoints to not use these fields
- Migration now runs cleanly on container start
- No manual intervention needed for production deployment
2026-03-27 07:48:23 +01:00
8be87bfdfb fix: Remove broken table_exists check
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Removed faulty EXISTS check that was causing "0" error.
Added debug logging and better error messages.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 07:34:29 +01:00
bbee44ecdc fix: Better error handling for goal types loading
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- Check if goal_type_definitions table exists
- Detailed error messages
- Fallback if goalTypes is empty
- Prevent form opening without types

Helps debugging Migration 024 issues.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 07:28:14 +01:00
65ee5f898f feat: Phase 1.5 - Flexible Goal System (DB-Registry) Part 1/2
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KRITISCHE ARCHITEKTUR-ÄNDERUNG vor Phase 0b:
Ermöglicht dynamische Goal Types ohne Code-Änderungen.

Backend:
- Migration 024: goal_type_definitions Tabelle
  → 8 existierende Typen als Seed-Data migriert
  → Flexible Schema: source_table, aggregation_method, calculation_formula
  → System vs. Custom Types (is_system flag)
- goal_utils.py: Universal Value Fetcher
  → get_current_value_for_goal() ersetzt hardcoded if/elif chain
  → Unterstützt: latest, avg_7d, avg_30d, sum_30d, count_7d, etc.
  → Komplexe Formeln (lean_mass) via calculation_formula JSON
- goals.py: CRUD API für Goal Type Definitions
  → GET /goals/goal-types (public)
  → POST/PUT/DELETE /goals/goal-types (admin-only)
  → Schutz für System-Types (nicht löschbar)
- goals.py: _get_current_value_for_goal_type() delegiert zu Universal Fetcher

Frontend:
- api.js: 4 neue Funktionen (listGoalTypeDefinitions, create, update, delete)

Dokumentation:
- TODO_GOAL_SYSTEM.md: Phase 1.5 hinzugefügt, Roadmap aktualisiert

Part 2/2 (nächster Commit):
- Frontend: Dynamic Goal Types Dropdown
- Admin UI: Goal Type Management Page
- Testing

Warum JETZT (vor Phase 0b)?
- Phase 0b Platzhalter (120+) nutzen Goals für Score-Berechnungen
- Flexible Goals → automatisch in Platzhaltern verfügbar
- Später umbauen = Doppelarbeit (alle Platzhalter anpassen)

Zukünftige Custom Goals möglich:
- 🧘 Meditation (min/Tag)
- 📅 Trainingshäufigkeit (x/Woche)
- 📊 Planabweichung (%)
- 🎯 Ritual-Adherence (%)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 06:45:05 +01:00
27a8af7008 debug: Add logging and warnings for Goal System issues
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Based on test feedback - 3 issues addressed:

1. Primary Toggle (Frontend Debug):
   - Add console.log in handleSaveGoal
   - Shows what data is sent to backend
   - Helps debug if checkbox state is correct

2. Lean Mass Display (Backend Debug):
   - Add error handling in lean_mass calculation
   - Log why calculation fails (missing weight/bf data)
   - Try-catch for value conversion errors

3. BP/Strength/Flexibility Warning (UI):
   - Yellow warning box for incomplete goal types
   - BP: "benötigt 2 Werte (geplant für v2.0)"
   - Strength/Flexibility: "Keine Datenquelle"
   - Transparent about limitations

Next: User re-tests with debug output to identify root cause.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 06:24:40 +01:00
87464ff138 fix: Phase 1 - Goal System Quick Fixes + Abstraction Layer
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Behebt 4 kritische Bugs in Phase 0a und schafft Basis für Phase 0b
ohne spätere Doppelarbeit.

Backend:
- NEW: goal_utils.py mit get_focus_weights() Abstraction Layer
  → V1: Mappt goal_mode zu Gewichten
  → V2 (später): Liest aus focus_areas Tabelle
  → Phase 0b Platzhalter (120+) müssen NICHT umgeschrieben werden
- FIX: Primary goal toggle in goals.py (is_primary im GoalUpdate Model)
  → Beim Update auf primary werden andere Goals korrekt auf false gesetzt
- FIX: lean_mass current_value Berechnung implementiert
  → weight - (weight * body_fat_pct / 100)
- FIX: VO2Max Spaltenname vo2_max (statt vo2max)
  → Internal Server Error behoben

CLAUDE.md:
- Version Update: Phase 1 Fixes (27.03.2026)

Keine Doppelarbeit:
- Alle zukünftigen Phase 0b Platzhalter nutzen get_focus_weights()
- v2.0 Redesign = nur eine Funktion ändern, nicht 120+ Platzhalter

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 06:13:47 +01:00