3 Commits

Author	SHA1	Message	Date
Lars	0c4264de44	feat: display_name + placeholder picker for prompts (Issue #28) ... 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
Lars	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
Lars	b4a1856f79	refactor: modular backend architecture with 14 router modules ... Phase 2 Complete - Backend Refactoring: - Extracted all endpoints to dedicated router modules - main.py: 1878 → 75 lines (-96% reduction) - Created modular structure for maintainability Router Structure (60 endpoints total): ├── auth.py - 7 endpoints (login, logout, password reset) ├── profiles.py - 7 endpoints (CRUD + current user) ├── weight.py - 5 endpoints (tracking + stats) ├── circumference.py - 4 endpoints (body measurements) ├── caliper.py - 4 endpoints (skinfold tracking) ├── activity.py - 6 endpoints (workouts + Apple Health import) ├── nutrition.py - 4 endpoints (diet + FDDB import) ├── photos.py - 3 endpoints (progress photos) ├── insights.py - 8 endpoints (AI analysis + pipeline) ├── prompts.py - 2 endpoints (AI prompt management) ├── admin.py - 7 endpoints (user management) ├── stats.py - 1 endpoint (dashboard stats) ├── exportdata.py - 3 endpoints (CSV/JSON/ZIP export) └── importdata.py - 1 endpoint (ZIP import) Core modules maintained: - db.py: PostgreSQL connection + helpers - auth.py: Auth functions (hash, verify, sessions) - models.py: 11 Pydantic models Benefits: - Self-contained modules with clear responsibilities - Easier to navigate and modify specific features - Improved code organization and readability - 100% functional compatibility maintained - All syntax checks passed Updated CLAUDE.md with new architecture documentation. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-19 11:15:35 +01:00