21 Commits

Author	SHA1	Message	Date
Lars	6cdc159a94	fix: add missing Header import in prompts.py ... NameError: name 'Header' is not defined Added Header to fastapi imports for export endpoints auth fix. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-29 21:25:33 +02:00
Lars	650313347f	feat: Placeholder Metadata V2 - Normative Implementation + ZIP Export Fix ... MAJOR CHANGES: - Enhanced metadata schema with 7 QA fields - Deterministic derivation logic (no guessing) - Conservative inference (prefer unknown over wrong) - Real source tracking (skip safe wrappers) - Legacy mismatch detection - Activity quality filter policies - Completeness scoring (0-100) - Unresolved fields tracking - Fixed ZIP/JSON export auth (query param support) FILES CHANGED: - backend/placeholder_metadata.py (schema extended) - backend/placeholder_metadata_enhanced.py (NEW, 418 lines) - backend/generate_complete_metadata_v2.py (NEW, 334 lines) - backend/tests/test_placeholder_metadata_v2.py (NEW, 302 lines) - backend/routers/prompts.py (V2 integration + auth fix) - docs/PLACEHOLDER_METADATA_VALIDATION.md (NEW, 541 lines) PROBLEMS FIXED: ✓ value_raw extraction (type-aware, JSON parsing) ✓ Units for dimensionless values (scores, correlations) ✓ Safe wrappers as sources (now skipped) ✓ Time window guessing (confidence flags) ✓ Legacy inconsistencies (marked with flag) ✓ Missing quality filters (activity placeholders) ✓ No completeness metric (0-100 score) ✓ Orphaned placeholders (tracked) ✓ Unresolved fields (explicit list) ✓ ZIP/JSON export auth (query token support for downloads) AUTH FIX: - export-catalog-zip now accepts token via query param (?token=xxx) - export-values-extended now accepts token via query param - Allows browser downloads without custom headers Konzept: docs/PLACEHOLDER_METADATA_REQUIREMENTS_V2_NORMATIVE.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-29 21:23:37 +02:00
Lars	087e8dd885	feat: Add Placeholder Metadata Export to Admin Panel ... 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
Lars	a04e7cc042	feat: Complete Placeholder Metadata System (Normative Standard v1.0.0) ... 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
Lars	f37936c84d	feat: show all stage outputs as collapsible JSON in expert mode ... Backend: - Add ALL stage outputs to metadata (not just referenced ones) - Format JSON with indent for readability - Description: 'Zwischenergebnis aus Stage X' Frontend: - Stage raw values shown in collapsible <details> element - JSON formatted in <pre> tag with syntax highlighting - 'JSON anzeigen ▼' summary for better UX Fixes: Stage X - Rohdaten now shows intermediate results	2026-03-26 13:17:58 +01:00
Lars	adb5dcea88	feat: category grouping in value table (Issue #47) ... FEATURE: Gruppierung nach Kategorien - Wertetabelle jetzt nach Modulen/Kategorien gruppiert - Bessere Übersicht und Zuordnung der Werte BACKEND: Category Metadata - Für normale Platzhalter: Kategorie aus Catalog (Profil, Körper, Ernährung, etc.) - Für extrahierte Werte: "Stage X - [Output Name]" - Für Rohdaten: "Stage X - Rohdaten" - Fallback: "Sonstiges" FRONTEND: Grouped Display - sortedCategories: Sortierung (Normal → Stage Outputs → Rohdaten) - Section Headers: Grauer Hintergrund mit Kategorie-Name - React.Fragment für Gruppierung SORTIERUNG: 1. Normale Kategorien (Profil, Körper, Ernährung, Training, etc.) 2. Stage Outputs (Stage 1 - Body, Stage 1 - Nutrition, etc.) 3. Rohdaten (Stage 1 - Rohdaten, Stage 2 - Rohdaten) 4. Innerhalb: Alphabetisch BEISPIEL: ┌────────────────────────────────────────────┐ │ PROFIL │ ├────────────────────────────────────────────┤ │ name │ Lars │ Name des Nutzers │ │ age │ 55 │ Alter in Jahren │ ├────────────────────────────────────────────┤ │ KÖRPER │ ├────────────────────────────────────────────┤ │ weight_... │ 85.2 kg │ Aktuelles Gewicht │ │ bmi │ 26.6 │ Body Mass Index │ ├────────────────────────────────────────────┤ │ ERNÄHRUNG │ ├────────────────────────────────────────────┤ │ kcal_avg │ 1427... │ Durchschn. Kalorien│ │ protein... │ 106g... │ Durchschn. Protein │ ├────────────────────────────────────────────┤ │ STAGE 1 - BODY │ ├────────────────────────────────────────────┤ │ ↳ bmi │ 26.6 │ Aus Stage 1 (body) │ │ ↳ trend │ sinkend │ Aus Stage 1 (body) │ ├────────────────────────────────────────────┤ │ STAGE 1 - NUTRITION │ ├────────────────────────────────────────────┤ │ ↳ kcal_... │ 1427 │ Aus Stage 1 (nutr.)│ └────────────────────────────────────────────┘ Experten-Modus zusätzlich: ├────────────────────────────────────────────┤ │ STAGE 1 - ROHDATEN │ ├────────────────────────────────────────────┤ │ 🔬 stage...│ {"bmi"..│ Rohdaten Stage 1 │ └────────────────────────────────────────────┘ version: 9.10.0 (feature) module: prompts 2.5.0, insights 1.8.0	2026-03-26 12:59:52 +01:00
Lars	da803da816	feat: extract individual values from stage outputs (Issue #47) ... FEATURE: Basis-Analysen Einzelwerte Vorher: stage_1_body → {"bmi": 26.6, "weight": "85.2kg"} (1 Zeile) Jetzt: bmi → 26.6 (eigene Zeile) weight → 85.2kg (eigene Zeile) BACKEND: JSON-Extraktion - Stage outputs (JSON) → extract individual fields - extracted_values dict sammelt alle Einzelwerte - Deduplizierung: Gleiche Keys nur einmal - Flags: - is_extracted: true → Wert aus Stage-Output extrahiert - is_stage_raw: true → Rohdaten (JSON) nur Experten-Modus BEISPIEL Stage 1 Output: { "stage_1_body": { "bmi": 26.6, "weight": "85.2 kg", "trend": "sinkend" } } → Metadata: { "bmi": { value: "26.6", description: "Aus Stage 1 (stage_1_body)", is_extracted: true }, "weight": { value: "85.2 kg", description: "Aus Stage 1 (stage_1_body)", is_extracted: true }, "stage_1_body": { value: "{\"bmi\": 26.6, ...}", description: "Rohdaten Stage 1 (Basis-Analyse JSON)", is_stage_raw: true } } FRONTEND: Smart Filtering Normal-Modus: - Zeigt: Einzelwerte (bmi, weight, trend) - Versteckt: Rohdaten (stage_1_body JSON) - Filter: is_stage_raw === false Experten-Modus: - Zeigt: Alles (Einzelwerte + Rohdaten) - Rohdaten: Grauer Hintergrund + 🔬 Icon VISUAL Indicators: ↳ bmi → Extrahierter Wert (grün) weight → Normaler Platzhalter (accent) 🔬 stage_1_* → Rohdaten JSON (grau, klein, nur Experten) ERGEBNIS: ┌──────────────────────────────────────────┐ │ 📊 Verwendete Werte (8) (+2 ausgeblendet)│ │ ┌────────────────────────────────────────┐│ │ │ weight_aktuell │ 85.2 kg │ Gewicht ││ ← Normal │ │ ↳ bmi │ 26.6 │ Aus St..││ ← Extrahiert │ │ ↳ trend │ sinkend │ Aus St..││ ← Extrahiert │ └────────────────────────────────────────┘│ └──────────────────────────────────────────┘ Experten-Modus zusätzlich: │ 🔬 stage_1_body │ {"bmi":...│ Rohdaten││ ← JSON version: 9.9.0 (feature) module: prompts 2.4.0, insights 1.7.0	2026-03-26 12:55:53 +01:00
Lars	e799edbae4	feat: expert mode + stage outputs in value table (Issue #47) ... FEATURE: Experten-Modus 🔬 - Toggle-Button in Wertetabelle - Normal: Nur gefüllte Werte anzeigen - Experten: Alle Platzhalter inkl. leere/technische - Anzeige: "(+X ausgeblendet)" wenn Werte gefiltert - Button-Style: Accent wenn aktiv FILTER: Leere Werte ausblenden (Normal-Modus) - Filtert: '', 'nicht verfügbar', '[Nicht verfügbar]' - Zeigt nur relevante Nutzer-Daten - Experten-Modus zeigt alles FEATURE: Stage-Outputs in Wertetabelle ✅ ROOT CAUSE: stage_N_key Platzhalter hatten keine Werte - Stage-Outputs (z.B. stage_1_body) sind Basis-Analysen-Ergebnisse - Wurden nicht in cleaned_values gefunden (nur statische Platzhalter) FIX: - Collect stage outputs aus result.debug.stages[].output - Store als stage_N_key dict - Lookup: erst stage_outputs, dann cleaned_values - Description: "Output aus Stage X (Basis-Analyse)" - JSON-Werte automatisch serialisiert BEISPIEL Pipeline-Wertetabelle: ┌──────────────────────────────────────────────┐ │ 📊 Verwendete Werte (8) (+3 ausgeblendet) 🔬│ │ ┌──────────────────────────────────────────┐ │ │ │ weight_aktuell │ 85.2 kg │ Gewicht │ │ │ │ stage_1_body │ {"bmi":...│ Output...│ │ ← Stage output! │ │ stage_1_nutr... │ {"kcal"...│ Output...│ │ │ └──────────────────────────────────────────┘ │ └──────────────────────────────────────────────┘ AKTIVIERUNG Experten-Modus: 1. Analyse öffnen 2. "📊 Verwendete Werte" aufklappen 3. Button "🔬 Experten-Modus" klicken 4. Zeigt alle Platzhalter (auch leere stage outputs) version: 9.8.0 (feature) module: prompts 2.3.0, insights 1.6.0	2026-03-26 12:44:28 +01:00
Lars	15bd6cddeb	feat: untruncated values + smart base prompt display (Issue #47) ... FEATURE: Volle Werte (nicht abgeschnitten) - Backend holt ungekürzten Werte direkt von placeholder_resolver - get_placeholder_example_values() statt debug.resolved_placeholders - Debug bleibt gekürzt (100 chars), Metadata ungekürzt FEATURE: Smart Display für Basis-Prompts - Basis-Prompts mit JSON-Output: Nur Wertetabelle anzeigen - JSON-Output in Collapsible "Technische Daten" verschoben - Wertetabelle auto-expanded bei Basis-Prompts - Pipeline + Text-Prompts: Wie bisher (Content + Wertetabelle) UI: Bessere Wertetabelle - Werte: word-break + max-width (400px) → kein Overflow - Alle Spalten: verticalAlign top für bessere Lesbarkeit - Platzhalter: nowrap (keine Umbrüche) BEISPIEL: ┌─────────────────────────────────────────┐ │ ℹ️ Basis-Prompt Rohdaten │ │ [Technische Daten anzeigen ▼] │ │ │ │ 📊 Verwendete Werte (8) ▼ ← expanded │ │ ┌──────────────────────────────────────┐│ │ │ Platzhalter │ Vollständiger Wert... ││ │ │ kcal_avg │ 1427 kcal/Tag (Ø 30...││ ← ungekürzt │ └──────────────────────────────────────┘│ └─────────────────────────────────────────┘ version: 9.7.0 (feature) module: prompts 2.2.0, insights 1.5.0	2026-03-26 12:37:52 +01:00
Lars	4a2bebe249	fix: value table metadata + |d modifier + cursor insertion (Issues #47, #48) ... BUG: Wertetabelle wurde nicht angezeigt FIX: enable_debug=true wenn save=true (für metadata collection) - metadata wird nur gespeichert wenn debug aktiv - jetzt: debug or save → metadata immer verfügbar BUG: {{placeholder|d}} Modifier funktionierte nicht ROOT CAUSE: catalog wurde bei Exception nicht zu variables hinzugefügt FIX: - variables['_catalog'] = catalog (auch wenn None) - Warning-Log wenn catalog nicht geladen werden kann - Debug warning wenn |d ohne catalog verwendet BUG: Platzhalter in Pipeline-Stages am Ende statt an Cursor FIX: - stageTemplateRefs Map für alle Stage-Textareas - onClick + onKeyUp tracking für Cursor-Position - Insert at cursor: template.slice(0, pos) + placeholder + template.slice(pos) - Focus + Cursor restore nach Insert TECHNICAL: - prompt_executor.py: Besseres Exception Handling für catalog - UnifiedPromptModal.jsx: Refs für alle Template-Felder - prompts.py: enable_debug=debug or save version: 9.6.1 (bugfix) module: prompts 2.1.1	2026-03-26 12:04:20 +01:00
Lars	c0a50dedcd	feat: value table + {{placeholder|d}} modifier (Issue #47) ... FEATURE #47: Wertetabelle nach KI-Analysen - Migration 021: metadata JSONB column in ai_insights - Backend sammelt resolved placeholders mit descriptions beim Speichern - Frontend: Collapsible value table in InsightCard - Zeigt: Platzhalter | Wert | Beschreibung - Sortiert tabellarisch - Funktioniert für base + pipeline prompts FEATURE #48: {{placeholder|d}} Modifier - Syntax: {{weight_aktuell|d}} → "85.2 kg (Aktuelles Gewicht in kg)" - resolve_placeholders() erkennt |d modifier - Hängt description aus catalog an Wert - Fein-granulare Kontrolle pro Platzhalter (nicht global) - Optional: nur wo sinnvoll einsetzen TECHNICAL: - prompt_executor.py: catalog parameter durchgereicht - execute_prompt_with_data() lädt catalog via get_placeholder_catalog() - Catalog als _catalog in variables übergeben, in execute_prompt() extrahiert - Base + Pipeline Prompts unterstützen |d modifier EXAMPLE: Template: "Gewicht: {{weight_aktuell|d}}, Alter: {{age}}" Output: "Gewicht: 85.2 kg (Aktuelles Gewicht in kg), Alter: 55" version: 9.6.0 (feature) module: prompts 2.1.0, insights 1.4.0	2026-03-26 11:52:26 +01:00
Lars	555ff62b56	feat: global placeholder export with values (Settings page) ... Zentraler Export aller verfügbaren Platzhalter mit aktuellen Werten. Backend: - GET /api/prompts/placeholders/export-values - Returns all placeholders organized by category - Includes resolved values for current profile - Includes metadata (description, example) - Flat list + categorized structure Frontend SettingsPage: - Button "📊 Platzhalter exportieren" - Downloads: placeholders-{profile}-{date}.json - Shows all 38+ placeholders with current values - Useful for: - Understanding available data - Debugging prompt templates - Verifying placeholder resolution Frontend api.js: - exportPlaceholderValues() Export Format: { "export_date": "2026-03-26T...", "profile_id": "...", "count": 38, "all_placeholders": { "name": "Lars", ... }, "placeholders_by_category": { "Profil": [...], "Körper": [...], ... } } Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-26 10:05:11 +01:00
Lars	7f94a41965	feat: batch import/export for prompts (Issue #28 Debug B) ... Dev→Prod Sync in 2 Klicks: Export → Import Backend: - GET /api/prompts/export-all → JSON mit allen Prompts - POST /api/prompts/import?overwrite=true/false → Import + Create/Update - Returns: created, updated, skipped counts - Validates JSON structure - Handles stages JSON conversion Frontend AdminPromptsPage: - Button "📦 Alle exportieren" → downloads all-prompts-{date}.json - Button "📥 Importieren" → file upload dialog - User-Prompt: Überschreiben? Ja/Nein - Success-Message mit Statistik (created/updated/skipped) Frontend api.js: - exportAllPrompts() - importPrompts(data, overwrite) Use Cases: 1. Backup: Prompts als JSON sichern 2. Dev→Prod: Auf dev.mitai entwickeln → exportieren → auf mitai.jinkendo importieren 3. Versionierung: Prompts in Git speichern Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-26 09:44:08 +01:00
Lars	97e57481f9	fix: Analysis page now uses unified prompt executor (Issue #28) ... BREAKING: Analysis page switched from old /insights/run to new /prompts/execute Changes: - Backend: Added save=true parameter to /prompts/execute - When enabled, saves final output to ai_insights table - Extracts content from pipeline output (last stage) - Frontend api.js: Added save parameter to executeUnifiedPrompt() - Frontend Analysis.jsx: Switched from api.runInsight() to api.executeUnifiedPrompt() - Transforms new result format to match InsightCard expectations - Pipeline outputs properly extracted and displayed Fixes: PIPELINE_MASTER responses (old template being sent to AI) The old /insights/run endpoint used raw template field, which for the legacy "pipeline" prompt was literally "PIPELINE_MASTER". The new executor properly handles stages and data processing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-26 09:38:58 +01:00
Lars	7f2ba4fbad	feat: debug system for prompt execution (Issue #28) ... - 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>	2026-03-26 08:01:33 +01:00
Lars	7be7266477	feat: unified prompt executor - Phase 2 complete (Issue #28) ... Backend: - prompt_executor.py: Universal executor for base + pipeline prompts - Dynamic placeholder resolution - JSON output validation - Multi-stage parallel execution (sequential impl) - Reference and inline prompt support - Data loading per module (körper, ernährung, training, schlaf, vitalwerte) Endpoints: - POST /api/prompts/execute - Execute unified prompts - POST /api/prompts/unified - Create unified prompts - PUT /api/prompts/unified/{id} - Update unified prompts Frontend: - api.js: executeUnifiedPrompt, createUnifiedPrompt, updateUnifiedPrompt Next: Phase 3 - Frontend UI consolidation	2026-03-25 14:52:24 +01:00
Lars	6627b5eee7	feat: Pipeline-System - Backend Infrastructure (Issue #28, Phase 1) ... 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
Lars	5e7ef718e0	fix: placeholder picker improvements + insight display names (Issue #28) ... Backend: - get_placeholder_catalog(): grouped placeholders with descriptions - Returns {category: [{key, description, example}]} format - Categories: Profil, Körper, Ernährung, Training, Schlaf, Vitalwerte, Zeitraum Frontend - Placeholder Picker: - Grouped by category with visual separation - Search/filter across keys and descriptions - Hover effects for better UX - Insert at cursor position (not at end) - Shows: key + description + example value - 'Keine Platzhalter gefunden' message when filtered Frontend - Insight Display Names: - InsightCard receives prompts array - Finds matching prompt by scope/slug - Shows prompt.display_name instead of hardcoded SLUG_LABELS - History tab also shows display_name in group headers - Fallback chain: display_name → SLUG_LABELS → scope User-facing improvements: ✓ Platzhalter zeigen echte Daten statt Zahlen ✓ Durchsuchbar + filterbar ✓ Einfügen an Cursor-Position ✓ Insights zeigen custom Namen (z.B. '🍽️ Meine Ernährung') Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-25 06:44:22 +01:00
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