31 Commits

Author	SHA1	Message	Date
Lars	10d24bbef7	fix(workflow): Duplicate - JSON-encode JSONB fields ... **Error:** ``` psycopg2.ProgrammingError: can't adapt type 'dict' ``` **Root Cause:** - duplicate_prompt passed Python dicts directly to SQL INSERT - JSONB fields from r2d() are already deserialized by psycopg2 - PostgreSQL expects JSON strings for JSONB columns **Fix:** - Added json.dumps() for all JSONB fields before INSERT: - stages, output_schema, question_augmentations, graph_data - Same pattern as import function Files changed: - backend/routers/prompts.py: JSON-encode JSONB in duplicate_prompt Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-11 14:46:13 +02:00
Lars	ff8104a533	fix(workflow): Route precedence - move export/import before path param ... **Root Cause:** - FastAPI route matching: /{prompt_id} caught ALL requests including /export-all - Specific routes MUST be defined BEFORE path parameter routes **Error:** ``` psycopg2.errors.InvalidTextRepresentation: invalid input syntax for type uuid: "export-all" LINE 1: SELECT * FROM ai_prompts WHERE id='export-all' ``` **Fix:** - Moved /export-all and /import endpoints to line 106 (BEFORE /{prompt_id} at ~260) - Added warning comments to both functions - Fixed typo: for r in → for row in **Affected:** - /export-all: Internal Server Error → now works ✅ - /import: Would have had same issue → preemptively fixed ✅ Files changed: - backend/routers/prompts.py: Reordered route definitions Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-11 14:42:55 +02:00
Lars	ba773e677b	fix(workflow): Test-Suite Fixes - Issues #5, #8, #9, #11, #12 ... Addressed test results from Test_status_Wkf.md: **Issue #5: End-Node Überschriften** - Fixed aggregate_results to show node labels instead of "Node 10" - Added graph lookup to get node.data.label from node objects - Modified backend/workflow_executor.py (2 locations) **Issue #8: Löschen-Taste funktioniert nicht** - Added Delete key support to WorkflowCanvas - Set deleteKeyCode={['Backspace', 'Delete']} - Frontend: WorkflowCanvas.jsx **Issue #9: Mehrere End-Nodes verhindern** - Added validation error when multiple End-Nodes exist - Backend supports only 1 End-Node (aggregate_results takes last) - Frontend: workflowValidation.js **Issue #11: Export Fehler "Internal Server Error"** - Added missing fields to export-all endpoint: - graph_data (workflow node graph) - question_augmentations (analysis prompts) - Added missing fields to import endpoint - Proper JSON serialization for all JSONB fields - Backend: routers/prompts.py **Issue #12: Workflow duplizieren funktioniert nicht** - Fixed duplicate endpoint to include all prompt fields: - type, stages, output_format, output_schema - question_augmentations, graph_data (critical for workflows!) - Backend: routers/prompts.py Files changed: - backend/workflow_executor.py: Node label lookup in aggregate_results - backend/routers/prompts.py: Export/import/duplicate fixes - frontend/src/components/workflow/WorkflowCanvas.jsx: Delete key - frontend/src/utils/workflowValidation.js: Max 1 End-Node validation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-11 14:15:57 +02:00
Lars	d803f39de3	feat: Refactor workflow result handling in prompts and analysis components ... - Introduced a new utility function to streamline the extraction of user-facing content from aggregated workflow results. - Updated backend prompt handling to utilize the new function for improved clarity and maintainability. - Adjusted frontend analysis component to leverage the utility for consistent content display across different workflow result formats. These changes enhance the overall user experience by ensuring more reliable and readable output from workflow executions.	2026-04-11 12:04:35 +02:00
Lars	300d96a9d8	feat: Enhance prompt execution for workflows and analysis offers ... - Added support for handling aggregated results in workflow prompts, allowing for various data formats (string, object). - Introduced a utility function to filter active prompts for both pipeline and workflow types in the analysis page. - Updated content handling in the analysis component to accommodate new workflow data structures. This improves the flexibility and usability of the prompt execution process in both backend and frontend components.	2026-04-11 11:42:54 +02:00
Lars	1a9fb99411	fix: FastAPI routing conflict for /placeholders endpoint ... Backend: - Moved /placeholders endpoint BEFORE /{prompt_id} catch-all - Prevents "placeholders" being parsed as UUID parameter - Fixes 500 Internal Server Error preventing placeholder loading Frontend: - PlaceholderPicker can now load ~120+ system placeholders Root Cause: - FastAPI matches routes in order - Generic /{prompt_id} was catching /placeholders first - psycopg2 error: invalid input syntax for type uuid: "placeholders" Version: 0.9p (workflow module) Part 3: End Node Template Engine Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-09 16:19:46 +02:00
Lars	d9bcaaaac6	fix: Add missing GET /api/prompts/{id} endpoint ... Critical Backend Bug: - Frontend calls api.getPrompt(id) → GET /api/prompts/{uuid} - Backend had NO endpoint for single prompt retrieval by ID - Result: 405 Method Not Allowed Backend Endpoints Before: ✓ GET /api/prompts - List all ✓ POST /api/prompts - Create ✓ PUT /api/prompts/{id} - Update ✗ GET /api/prompts/{id} - MISSING! Backend Endpoints After: ✓ GET /api/prompts - List all ✓ GET /api/prompts/{id} - Get single (NEW) ✓ POST /api/prompts - Create ✓ PUT /api/prompts/{id} - Update Implementation: - Added get_prompt(prompt_id: str) function - Returns single prompt by UUID - 404 if not found - Requires auth (admin or user) This fixes: - Workflow loading after save (loadWorkflow calls getPrompt) - Workflow editing from admin list (Edit button calls getPrompt) - All 405 Method Not Allowed errors Root Cause: Backend was incomplete, missing basic CRUD read-by-id endpoint	2026-04-04 22:43:07 +02:00
Lars	7d22b052dd	fix: Phase 5 - Workflow save + node persistence bugs ... 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
Lars	81681f0de3	fix: Handle missing TimeWindow enum in export endpoint ... Error: NameError TimeWindow not defined Fix: Graceful degradation if old metadata enums not available Gap report now optional (empty if old system unavailable) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 11:54:02 +02:00
Lars	645967a2ab	feat: Placeholder Registry Framework + Part A Nutrition Metrics ... Part A Implementation (Nutrition Basis Metrics): - Registry-based metadata system (flexible, not hardcoded) - 4 placeholders registered: kcal_avg, protein_avg, carb_avg, fat_avg - Evidence-based tagging (code-derived, draft-derived, unresolved, to_verify) - Single source of truth for all consumers (Prompt, GUI, Export, Validation) Technical: - backend/placeholder_registry.py: Core registry framework - backend/placeholder_registrations/nutrition_part_a.py: Part A registrations - backend/placeholder_registry_export.py: Export integration - backend/routers/prompts.py: /placeholders/export-values-extended integration Metadata completeness: - 22 metadata fields per placeholder - Evidence tracking for all fields - Architecture alignment (Layer 1/2a/2b) NO LOGIC CHANGE: - Data Layer unchanged (nutrition_metrics.py) - Resolver unchanged (placeholder_resolver.py) - Values identical (only metadata/export enhanced) Breaking Change Risk: NONE Deploy Risk: VERY LOW (only export enhancement) Plan: .claude/task/rework_0b_placeholder/NUTRITION_PART_A_CHANGE_PLAN.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 11:46:16 +02:00
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