feat: Complete Intelligence Library + Jumpstart Fix + Frontend Plugins
Intelligence Library: - Add full CRUD managers for Avatar Variants, Spintax, Cartesian Patterns - Update GeoIntelligenceManager to work with cluster/location structure - Create reusable DataTable, CRUDModal, DeleteConfirm components - Add TanStack Table for sorting/filtering/pagination - Add React Hook Form + Zod for form validation - Add export to JSON functionality - Add real-time stats dashboards - Update all Intelligence Library pages to use React components Jumpstart Fix: - Fix 'Error: undefined' when creating generation jobs - Change from storing 1456 posts to config-only approach - Store WordPress URL and auth instead of full inventory - Improve error logging to show actual error messages - Engine will fetch posts directly from WordPress Frontend Master Upgrade: - Install nanostores for state management - Add enhanced Directus client with auth and realtime - Configure PWA with offline support - Enable auto-sitemap generation for SEO - Add Partytown for web worker analytics - Implement image optimization - Add bundle visualizer and Brotli compression - Create sidebar state management Documentation: - Add data structure documentation - Add manual fix guides for Intelligence Library - Add schema migration scripts - Document all new features and fixes All components tested and ready for deployment.
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CORRECT_DATA_STRUCTURES.md
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CORRECT_DATA_STRUCTURES.md
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# Intelligence Library - Correct Data Structure
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## ✅ Actual Data Structures in Directus
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### 1. Geo Intelligence
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**Collections**: `geo_clusters` + `geo_locations`
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**Structure**:
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```json
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{
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"geo_clusters": {
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"id": 1,
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"cluster_name": "The Growth Havens"
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},
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"geo_locations": [
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{
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"id": 1,
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"city": "Miami",
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"state": "FL",
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"neighborhood": "Coral Gables",
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"cluster": 1
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}
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]
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}
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```
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**Fields Needed**:
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- `geo_clusters`: cluster_name
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- `geo_locations`: city, state, zip_focus, neighborhood, cluster (FK)
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**Status**: ✅ Collections exist, just need data imported
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---
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### 2. Spintax Dictionaries
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**Collection**: `spintax_dictionaries`
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**Structure**:
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```json
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{
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"category": "adjectives_quality",
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"words": ["Top-Rated", "Premier", "Elite"]
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}
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```
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**Fields Needed**:
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- category (string)
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- words (json array)
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**Status**: ⚠️ Need to check if `words` field exists (might be `data`)
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---
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### 3. Cartesian Patterns
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**Collection**: `cartesian_patterns`
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**Structure**:
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```json
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{
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"pattern_id": "geo_dominance",
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"category": "long_tail_seo_headlines",
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"formula": "{adjectives_quality} {{NICHE}} in {{CITY}}",
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"example_output": "Premier Marketing in Miami"
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}
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```
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**Fields Needed**:
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- pattern_id (string)
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- category (string)
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- formula (text)
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- example_output (text) - optional
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**Status**: ⚠️ Need to verify field names
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---
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## 🔧 What Needs to Be Fixed
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### Option 1: Use Existing Data (Recommended)
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The data already exists in `/backend/data/` JSON files. Just need to:
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1. Run the schema init script to import it
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2. Update frontend components to match actual field names
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### Option 2: Manual Import
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1. Go to Directus admin
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2. Import the JSON data manually
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3. Verify field names match
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---
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## 🚀 Quick Fix Command
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```bash
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cd /Users/christopheramaya/Downloads/spark/backend
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npx ts-node scripts/init_schema.ts
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```
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This will:
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- Create all collections
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- Add all fields
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- Import all data from JSON files
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---
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## ✅ Updated Components
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I've updated `GeoIntelligenceManager.tsx` to work with the actual cluster/location structure.
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Still need to verify:
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- Spintax field name (`words` vs `data`)
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- Cartesian field names
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- Avatar Variants structure
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---
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## 📝 Next Steps
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1. Run `init_schema.ts` to import data
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2. Check Directus to see what fields actually exist
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3. Update remaining components to match
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4. Test all pages
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