Commit Graph

13 Commits

Author SHA1 Message Date
df0165bee3 feat: add relaxed arm circumference measurement and update related features
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- Introduced `c_arm_relaxed` to the CircumferenceEntry model for tracking relaxed arm measurements.
- Updated database schema to include `c_arm_relaxed` in the circumference_log table.
- Implemented calculation for 28-day relaxed arm circumference change with `calculate_arm_relaxed_28d_delta`.
- Enhanced placeholder resolver and registration to support new relaxed arm measurement.
- Updated frontend components to accommodate the new measurement, including forms and CSV exports.
- Improved documentation and guide data to reflect the addition of relaxed arm measurements.
2026-04-19 10:34:51 +02:00
766b64cd64 feat: Expand ActivityEntry model and enhance activity log handling
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- Added new fields to the ActivityEntry model for improved tracking: hr_min, pace_min_per_km, cadence, avg_power, elevation_gain, temperature_celsius, humidity_percent, avg_hr_percent, and kcal_per_km.
- Updated the create_activity function to accommodate the new fields in the activity log.
- Modified session metrics handling to ensure accurate data retrieval and merging based on the updated schema.
2026-04-14 12:59:47 +02:00
48508c164e feat: Add Activity Session Metrics functionality
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- Introduced Activity Session Metrics for enhanced tracking of session data.
- Updated backend to support new API endpoints for managing session metrics.
- Added new Pydantic models for activity metrics and replaced metrics functionality.
- Enhanced data layer to include session metrics in recent training session data.
- Updated documentation to reflect changes in session metrics handling.
2026-04-14 11:49:14 +02:00
c63ec5f700 feat: Enhance profile update functionality with email validation and improved error handling
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2026-04-05 11:14:01 +02:00
7d22b052dd fix: Phase 5 - Workflow save + node persistence bugs
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KRITISCHE FIXES:

1. Backend: Workflow-Type Support
   - models.py: graph_data Feld hinzugefügt
   - models.py: slug Optional (auto-generiert)
   - prompts.py: 'workflow' in erlaubten Typen
   - prompts.py: graph_data in INSERT/UPDATE
   - prompts.py: Auto-Slug-Generierung aus Name
   - FIX: "Field required: slug" Error behoben

2. Frontend: Node-Updates Persistence
   - selectedNode sync mit nodes array (useEffect)
   - FIX: Änderungen gingen verloren (stale state)
   - FIX: Prompt-Auswahl nicht sichtbar nach Edit
   - FIX: Fallback-Strategy nicht gespeichert
   - FIX: Node-Name Änderungen nicht übernommen

BEHOBEN:
-  Save fehlgeschlagen →  Workflows speicherbar
-  Node-Name ignoriert →  Live-Update
-  Prompt verschwindet →  Bleibt sichtbar
-  Fallback nicht saved →  Persistiert

Tested: Backend API akzeptiert jetzt type='workflow'

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-04 19:17:41 +02:00
2e0838ca08 feat: unified prompt system migration schema (Issue #28 Phase 1)
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- Migration 020: Add type, stages, output_format columns to ai_prompts
- Migrate existing prompts to 1-stage pipeline format
- Migrate pipeline_configs into ai_prompts as multi-stage pipelines
- Add UnifiedPrompt Pydantic models for new API
- Backup pipeline_configs table (keep during transition)

Schema structure:
- type: 'base' (reusable) or 'pipeline' (multi-stage)
- stages: JSONB array [{stage:1, prompts:[{source, slug, template, output_key, output_format}]}]
- output_format: 'text' or 'json'
- output_schema: JSON validation schema (optional)

Next: Backend executor + Frontend UI consolidation
2026-03-25 10:43:10 +01:00
6627b5eee7 feat: Pipeline-System - Backend Infrastructure (Issue #28, Phase 1)
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Implementiert konfigurierbare mehrstufige Analysen. Admins können
mehrere Pipeline-Konfigurationen erstellen mit unterschiedlichen
Modulen, Zeiträumen und Prompts.

**Backend:**
- Migration 019: pipeline_configs Tabelle + ai_prompts erweitert
- Pipeline-Config Models: PipelineConfigCreate, PipelineConfigUpdate
- Pipeline-Executor: refactored für config-basierte Ausführung
- CRUD-Endpoints: /api/prompts/pipeline-configs (list, create, update, delete, set-default)
- Reset-to-Default: /api/prompts/{id}/reset-to-default für System-Prompts

**Features:**
- 3 Seed-Configs: "Alltags-Check" (default), "Schlaf & Erholung", "Wettkampf-Analyse"
- Dynamische Platzhalter: {{stage1_<slug>}} für alle Stage-1-Ergebnisse
- Backward-compatible: /api/insights/pipeline ohne config_id nutzt default

**Dateien:**
- backend/migrations/019_pipeline_system.sql
- backend/models.py (PipelineConfigCreate, PipelineConfigUpdate)
- backend/routers/insights.py (analyze_pipeline refactored)
- backend/routers/prompts.py (Pipeline-Config CRUD + Reset-to-Default)

**Nächste Schritte:**
- Frontend: Pipeline-Config Dialog + Admin-UI
- Design: Mobile-Responsive + Icons

Issue #28 Progress: Backend 3/3  | Frontend 0/3 🔲 | Design 0/3 🔲

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-25 09:42:28 +01:00
0c4264de44 feat: display_name + placeholder picker for prompts (Issue #28)
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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>
2026-03-25 06:31:25 +01:00
500de132b9 feat: AI-Prompts flexibilisierung - Backend & Admin UI (Issue #28, Part 1)
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>
2026-03-24 15:32:25 +01:00
302948a248 fix: add quality_filter_level to ProfileUpdate model (Issue #31)
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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>
2026-03-24 06:44:05 +01:00
410b2ce308 feat(v9d): add training types system + logout button
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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>
2026-03-21 13:05:33 +01:00
c1562a27f4 feat: add self-registration with email verification
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>
2026-03-21 09:53:11 +01:00
c7d283c0c9 refactor: extract Pydantic models to models.py
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Phase 1.3 - Data Models isolieren

NEUE DATEI:
- backend/models.py: Alle Pydantic Models (122 Zeilen)
  * ProfileCreate, ProfileUpdate
  * WeightEntry, CircumferenceEntry, CaliperEntry
  * ActivityEntry, NutritionDay
  * LoginRequest, PasswordResetRequest, PasswordResetConfirm
  * AdminProfileUpdate

ÄNDERUNGEN:
- backend/main.py:
  * Import models from models.py
  * Entfernt: ~60 Zeilen Model-Definitionen
  * Von 2025 → 1878 Zeilen (-147 Zeilen / -7%)

PROGRESS:
 db.py: Database + init_db
 auth.py: Auth functions + dependencies
 models.py: Pydantic schemas

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-19 09:53:51 +01:00