BUG: Wertetabelle wurde nicht angezeigt bei neuer Analyse
ROOT CAUSE: newResult hatte nur {scope, content}, kein metadata
FIX: Build metadata from result.debug.resolved_placeholders
- Für Base: direkt aus resolved_placeholders
- Für Pipeline: collect aus allen stages
- Metadata structure: {prompt_type, placeholders: {key: {value, description}}}
NOTE: Immediate preview hat keine descriptions (nur values)
Saved insights (nach loadAll) haben full metadata with descriptions aus DB
version: 9.6.2 (bugfix)
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
Problem: dob Spalte ist DATE (PostgreSQL) → Python bekommt datetime.date,
nicht String → strptime() schlägt fehl → age = "unbekannt"
Fix: Prüfe isinstance(dob, str) und handle beide Typen:
- String → strptime()
- date object → direkt verwenden
Jetzt funktioniert {{age}} Platzhalter korrekt.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Added "📋 Platzhalter exportieren" button in debug viewer:
- Exports all resolved placeholders with values
- Includes all available_variables
- For pipelines: exports per-stage placeholder data
- JSON format with timestamp and prompt metadata
- Filename: placeholders-{slug}-{date}.json
Use case: Development aid - see exactly what data is available
for prompt templates without null values.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
- Removed conditional hiding of test button (prompt?.slug)
- Button now always visible with helpful tooltip
- handleTest already has save-check logic
Improves discoverability of test functionality.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- caliper_summary: use body_fat_pct (not bf_jpl)
- circ_summary: use c_chest, c_waist, c_hip (not brust, taille, huefte)
- get_latest_bf: use body_fat_pct for consistency
Fixes SQL errors when running base prompts that feed pipeline prompts.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- New placeholder: {{activity_detail}} returns formatted activity log
- Shows last 20 activities with date, type, duration, kcal, HR
- Makes activity analysis prompts work properly
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Placeholder resolver returns keys with {{ }} wrappers,
but resolve_placeholders expects clean keys.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Backend: integrate get_placeholder_example_values in execute_prompt_with_data
- Backend: now provides BOTH raw data AND processed placeholders
- Backend: unwrap Markdown-wrapped JSON (```json ... ```)
- Fixes old-style prompts that expect name, weight_trend, caliper_summary
Resolves unresolved placeholders issue.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Frontend: debug viewer now shows even when test fails
- Frontend: export button to download complete prompt config as JSON
- Backend: attach debug info to JSON validation errors
- Backend: include raw output and length in error details
Users can now debug failed prompts and export configs for analysis.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- 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>
- PlaceholderPicker: Example values in separate full-width row
- Analysis.jsx: Show only pipeline-type prompts
- Analysis.jsx: Remove base prompts and Prompts tab
- Cleanup: Remove PromptEditor component and unused imports
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Major improvements:
1. PlaceholderPicker component (new)
- Loads placeholders dynamically from backend catalog
- Grouped by categories: Profil, Körper, Ernährung, Training, etc.
- Search/filter functionality
- Shows live example values from user data
- Popup modal with expand/collapse categories
2. Replaced hardcoded placeholder chips
- 'Platzhalter einfügen' button opens picker
- Works in both base templates and pipeline inline templates
- Auto-closes after selection
3. Uses existing backend system
- GET /api/prompts/placeholders
- placeholder_resolver.py with PLACEHOLDER_MAP
- Dynamic, module-based placeholder system
- No manual updates needed when modules add new placeholders
Benefits:
- Scalable: New modules can add placeholders without frontend changes
- User-friendly: Search and categorization
- Context-aware: Shows real example values
- Future-proof: Backend-driven catalog
New features:
1. Placeholder chips now visible in pipeline inline templates
- Click to insert: weight_data, nutrition_data, activity_data, etc.
- Same UX as base prompts
2. Convert to Base Prompt button
- New icon (ArrowDownToLine) in actions column
- Only visible for 1-stage pipeline prompts
- Converts pipeline → base by extracting inline template
- Validates: must be 1-stage, 1-prompt, inline source
This allows migrated prompts to be properly categorized as base prompts
for reuse in other pipelines.
Fixes:
1. Template field in stages now full width (was too narrow)
2. Table horizontal scrollbar for mobile (overflow-x: auto)
3. Table min-width 900px to prevent icon clipping
4. Added clickable placeholder chips below base template
- Click to insert placeholders into template
- Shows: weight_data, nutrition_data, activity_data, sleep_data, etc.
UI now mobile-ready and more user-friendly.
Issue: template has NOT NULL constraint but pipeline-type prompts
don't use template (they use stages JSONB instead).
Solution: ALTER COLUMN template DROP NOT NULL before inserting
pipeline configs into ai_prompts.
Fixed Step 3 pipeline_configs migration:
- Simplified JSONB aggregation logic
- Properly scope pc alias in subqueries
- Use UNNEST with FROM clause for array expansion
Previous version had correlation issues with nested subqueries.
Current state:
- Pipeline configs working (migration 019)
- PipelineConfigModal complete
- AdminPromptsPage with tabs
- All Phase 1+2 features deployed and tested
Next: Consolidate into unified prompt system
- Single ai_prompts table for all types
- Dynamic stages (unlimited)
- Basis prompts + pipeline prompts
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>
- PromptEditModal: all inputs/textareas now full-width
- Labels positioned above fields (not inline)
- Text left-aligned (was right-aligned)
- Added resize:vertical for textareas
- Side-by-side comparison with word-wrap
- Follows app-wide form design pattern
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Frontend components:
- PromptEditModal.jsx: Full editor with preview, generator, optimizer
- PromptGenerator.jsx: KI-assisted prompt creation from goal description
- Extended api.js with 10 new prompt endpoints
Navigation:
- Added /admin/prompts route to App.jsx
- Added KI-Prompts section to AdminPanel with navigation button
Features complete:
✅ Admin can create/edit/delete/duplicate prompts
✅ Category filtering and reordering
✅ Preview prompts with real user data
✅ KI generates prompts from goal + example data
✅ KI analyzes and optimizes existing prompts
✅ Side-by-side comparison original vs optimized
Ready for testing: http://dev.mitai.jinkendo.de/admin/prompts
Issue #28 Phase 2 complete - 13-18h estimated, ~14h actual
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
