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New alert system and panel de control page

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Urtzi Alfaro
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# Dashboard Demo Seed Scripts
Comprehensive demo data seeding scripts for the JTBD-aligned dashboard.
## 🎯 Purpose
These scripts create realistic demo data to showcase all dashboard features and user flows:
- **Time-based Action Queue** (URGENT/TODAY/WEEK grouping)
- **AI Prevented Issues** (showcasing AI value)
- **Execution Progress Tracking** (production/deliveries/approvals)
- **Stock Receipt Modal** workflows
- **Health Status** tri-state checklist
- **All Alert Types** with full enrichment
## 📋 Available Scripts
### 1. `seed_dashboard_comprehensive.py` ⭐ **RECOMMENDED**
**Comprehensive dashboard demo covering ALL scenarios**
**What it seeds:**
- 🔴 **URGENT** actions (<6h deadline): 3 alerts
- PO approval escalation (72h aged, 2h deadline)
- Delivery overdue (4h late, supplier contact needed)
- Batch at risk (missing ingredients, 5h window)
- 🟡 **TODAY** actions (<24h deadline): 3 alerts
- PO approval needed (dairy products, 20h deadline)
- Delivery arriving soon (8h, prep required)
- Low stock warning (yeast, order today recommended)
- 🟢 **THIS WEEK** actions (<7d deadline): 2 alerts
- Weekend demand surge prediction
- Stock receipt incomplete (2 days old)
- ✅ **AI PREVENTED ISSUES**: 3 alerts
- Prevented stockout (PO created, €250 saved)
- Prevented waste (production adjusted, €120 saved)
- Prevented delay (batches rescheduled, €85 saved)
**Expected Dashboard State:**
```
Health Status: YELLOW (actions needed)
├─ ⚡ AI Handled: 3 issues (€455 saved)
└─ ⚠️ Needs You: 8 actions
Action Queue: 8 total actions
├─ 🔴 URGENT: 3
├─ 🟡 TODAY: 3
└─ 🟢 WEEK: 2
AI Impact: €455 in prevented costs
```
**Usage:**
```bash
# Quick start
python services/demo_session/scripts/seed_dashboard_comprehensive.py
# With custom tenant
DEMO_TENANT_ID=your-tenant-id python services/demo_session/scripts/seed_dashboard_comprehensive.py
# With custom RabbitMQ
RABBITMQ_URL=amqp://user:pass@host:5672/ python services/demo_session/scripts/seed_dashboard_comprehensive.py
```
---
### 2. `seed_enriched_alert_demo.py`
**Legacy enriched alert demo** (basic scenarios)
Seeds 5 basic alert types with automatic enrichment:
- Low stock (AI handled)
- Supplier delay (critical)
- Waste trend (standard)
- Forecast anomaly (info)
- Equipment maintenance (medium)
**Usage:**
```bash
python services/demo_session/scripts/seed_enriched_alert_demo.py
```
**Note:** For full dashboard testing, use `seed_dashboard_comprehensive.py` instead.
---
## 🚀 Quick Start
### Prerequisites
1. **RabbitMQ running:**
```bash
kubectl get pods | grep rabbitmq
# Should show: rabbitmq-0 1/1 Running
```
2. **Alert Processor service running:**
```bash
kubectl get pods -l app.kubernetes.io/name=alert-processor-service
# Should show: alert-processor-service-xxx 1/1 Running
```
3. **Python dependencies:**
```bash
pip install -r requirements.txt
```
### Running the Demo
```bash
# 1. Navigate to project root
cd /path/to/bakery-ia
# 2. Load environment variables (if needed)
source .env
# 3. Run comprehensive dashboard seeder
python services/demo_session/scripts/seed_dashboard_comprehensive.py
```
### Expected Output
```
================================================================================
🚀 SEEDING COMPREHENSIVE DASHBOARD DEMO DATA
================================================================================
📋 Configuration:
Tenant ID: demo-tenant-bakery-ia
RabbitMQ: amqp://guest:guest@localhost:5672/
📊 Dashboard Scenarios to Seed:
🔴 URGENT actions (<6h): 3
🟡 TODAY actions (<24h): 3
🟢 WEEK actions (<7d): 2
✅ AI Prevented Issues: 3
📦 Total Alerts: 11
📤 Publishing Alerts:
────────────────────────────────────────────────────────────────────────────────
1. ✅ [🔴 URGENT] URGENT: PO Approval Needed - Yeast Supplier
2. ✅ [🔴 URGENT] Delivery Overdue: Flour Delivery
3. ✅ [🔴 URGENT] Batch At Risk: Missing Ingredients
4. ✅ [🟡 TODAY] PO Approval: Butter & Dairy Products
5. ✅ [🟡 TODAY] Delivery Arriving in 8 Hours: Sugar & Ingredients
6. ✅ [🟡 TODAY] Low Stock: Fresh Yeast
7. ✅ [🟢 WEEK] Weekend Demand Surge Predicted
8. ✅ [🟢 WEEK] Stock Receipt Pending: Flour Delivery
9. ✅ [✅ PREVENTED] ✅ AI Prevented Stockout: Flour
10. ✅ [✅ PREVENTED] ✅ AI Prevented Waste: Reduced Monday Production
11. ✅ [✅ PREVENTED] ✅ AI Prevented Delay: Rescheduled Conflicting Batches
✅ Published 11/11 alerts successfully
================================================================================
🎉 DASHBOARD DEMO SEEDED SUCCESSFULLY!
================================================================================
```
---
## 🔍 Verification
### 1. Check Alert Processing
```bash
# View alert-processor logs (real-time)
kubectl logs -f deployment/alert-processor-service | grep 'enriched_alert'
# Should see:
# alert_enriched alert_id=xxx type_class=action_needed priority_score=92
# alert_enriched alert_id=xxx type_class=prevented_issue priority_score=35
```
### 2. Access Dashboard
```bash
# Port forward if needed
kubectl port-forward svc/frontend-service 3000:3000
# Open browser
open http://localhost:3000/dashboard
```
### 3. Verify Dashboard Sections
**✅ Health Status Card:**
- Should show YELLOW status
- Tri-state checklist items visible
- AI prevented issues badge showing "3 issues prevented"
**✅ Action Queue Card:**
- 🔴 URGENT section with 3 items (2h countdown visible)
- 🟡 TODAY section with 3 items
- 🟢 THIS WEEK section with 2 items
**✅ Orchestration Summary:**
- "User Needed: 8" in yellow (clickable)
- "AI Prevented: 3 issues" in green badge
**✅ AI Impact Card:**
- Shows €455 total savings
- Lists 3 prevented issues
---
## 🧪 Testing Scenarios
### Scenario 1: Urgent Action with Countdown
**Test:** PO Approval Escalation (2h deadline)
1. Navigate to dashboard
2. Find "URGENT: PO Approval Needed - Yeast Supplier" in 🔴 URGENT section
3. Verify countdown timer shows ~2 hours
4. Click "Approve" button
5. Verify alert moves to resolved/archived
**Expected Smart Actions:**
- ✅ Approve PO (primary, green)
- ⚙️ Modify PO (secondary)
- ❌ Reject PO (danger, red)
---
### Scenario 2: Stock Receipt Modal
**Test:** Mark Delivery as Received
1. Find "Delivery Arriving in 8 Hours" in 🟡 TODAY section
2. Click "Mark as Received" button
3. **Stock Receipt Modal should open:**
- Shows PO details (supplier, items)
- Lot input fields for each line item
- Quantity validation (lots must sum to actual)
- Mandatory expiration dates
4. Fill in lot details:
- Lot number (e.g., "LOT-2024-089")
- Quantity per lot
- Expiration date (required)
- Warehouse location
5. Click "Confirm Receipt"
6. Verify inventory is updated
**Expected Validation:**
- ❌ Error if lot quantities don't sum to actual quantity
- ❌ Error if expiration date missing
- ✅ Success toast on confirmation
---
### Scenario 3: AI Prevented Issue Showcase
**Test:** View AI Value Proposition
1. Find "✅ AI Prevented Stockout: Flour" in alert list
2. Verify prevented issue badge (⚡ lightning bolt)
3. Click to expand reasoning
4. **Should show:**
- AI action taken: "Purchase order created automatically"
- Savings: €250
- Reasoning: "Detected stock would run out in 1.8 days..."
- Business impact: "Secured 4 production batches"
5. Navigate to Orchestration Summary Card
6. Verify "AI Prevented: 3 issues" badge shows €455 total
---
### Scenario 4: Call Supplier (External Action)
**Test:** Supplier contact integration
1. Find "Delivery Overdue: Flour Delivery" in 🔴 URGENT section
2. Click "Call Supplier" button
3. **Expected behavior:**
- Phone dialer opens with +34-555-5678
- OR clipboard copies phone number
- Toast notification confirms action
**Metadata displayed:**
- Supplier: Harinera San José
- Phone: +34-555-5678
- Email: pedidos@harinerasj.es
- Hours overdue: 4
---
### Scenario 5: Navigation to Linked Pages
**Test:** Smart action navigation
1. Find "Batch At Risk: Missing Ingredients" in 🔴 URGENT
2. Click "View Production" button
3. **Should navigate to:** `/production?batch_id=batch-chocolate-cake-evening`
4. Production page shows batch details
5. Missing ingredients highlighted
---
## 🐛 Troubleshooting
### Issue: Alerts not appearing in dashboard
**Check:**
```bash
# 1. Verify RabbitMQ is running
kubectl get pods | grep rabbitmq
# 2. Check alert-processor logs
kubectl logs deployment/alert-processor-service --tail=100
# 3. Verify alerts.exchange exists
# (Check RabbitMQ management UI: localhost:15672)
# 4. Check for errors in seeder output
python services/demo_session/scripts/seed_dashboard_comprehensive.py 2>&1 | grep ERROR
```
**Common Fixes:**
- Restart alert-processor: `kubectl rollout restart deployment/alert-processor-service`
- Re-run seeder with debug: `python -u services/demo_session/scripts/seed_dashboard_comprehensive.py`
- Check RabbitMQ queue: `raw_alerts_queue` should have consumers
---
### Issue: Countdown timer not working
**Check:**
```bash
# Verify urgency_context.auto_action_countdown_seconds is set
# Should be in alert metadata
```
**Fix:** Re-run seeder to ensure urgency_context is populated
---
### Issue: Stock Receipt Modal not opening
**Check:**
```bash
# 1. Verify modal component is imported in DashboardPage
grep -r "StockReceiptModal" frontend/src/pages/app/DashboardPage.tsx
# 2. Check browser console for errors
# Look for: "delivery:mark-received event not handled"
# 3. Verify smartActionHandlers.ts is loaded
```
**Fix:** Ensure event listener is registered in DashboardPage.tsx
---
## 📊 Data Reference
### Alert Type Classes
- `action_needed` - Requires user decision (yellow)
- `prevented_issue` - AI already handled (blue/green)
- `trend_warning` - Proactive insight (info)
- `escalation` - Time-sensitive with countdown (red)
- `information` - Pure informational (gray)
### Priority Levels
- `critical` (90-100) - Needs decision in 2 hours
- `important` (70-89) - Needs decision today
- `standard` (50-69) - Review when convenient
- `info` (0-49) - For awareness
### Time Groups
- 🔴 **URGENT** - Deadline <6 hours
- 🟡 **TODAY** - Deadline <24 hours
- 🟢 **THIS WEEK** - Deadline <7 days
---
## 🔄 Resetting Demo Data
To clear all demo alerts and start fresh:
```bash
# 1. Delete all alerts for demo tenant
# (This requires admin access to alert-processor DB)
# 2. Or restart alert-processor (clears in-memory cache)
kubectl rollout restart deployment/alert-processor-service
# 3. Re-run seeder
python services/demo_session/scripts/seed_dashboard_comprehensive.py
```
---
## 📝 Notes
- **Automatic Enrichment:** All alerts are automatically enriched by alert-processor service
- **Priority Scoring:** Multi-factor algorithm considers urgency, impact, user agency
- **Smart Actions:** Dynamically generated based on alert type and context
- **Real-time Updates:** Dashboard subscribes to SSE for live alert updates
- **i18n Support:** All alerts support EN/ES/EU languages
---
## 🚀 Next Steps
After seeding:
1. **Test all smart actions** (approve, reject, call, navigate, etc.)
2. **Verify performance** (<500ms dashboard load time)
3. **Test responsive design** (mobile, tablet, desktop)
4. **Check translations** (switch language in UI)
5. **Test SSE updates** (create new alert, see real-time update)
---
## 🤝 Contributing
To add new demo scenarios:
1. Edit `seed_dashboard_comprehensive.py`
2. Add new alert to appropriate function (`create_urgent_actions()`, etc.)
3. Include full metadata for enrichment
4. Test enrichment output
5. Update this README with new scenario
---
## 📚 Related Documentation
- [Alert Type Schemas](../../../shared/schemas/alert_types.py)
- [Dashboard Service API](../../../services/orchestrator/app/api/dashboard.py)
- [Smart Action Handlers](../../../frontend/src/utils/smartActionHandlers.ts)
- [JTBD Implementation Status](../../../docs/JTBD-IMPLEMENTATION-STATUS.md)

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#!/usr/bin/env python3
"""
Comprehensive Dashboard Demo Seed Script
Seeds ALL dashboard scenarios to showcase the complete JTBD-aligned dashboard:
1. Health Status (green/yellow/red with tri-state checklist)
2. Unified Action Queue (URGENT/TODAY/WEEK time-based grouping)
3. Execution Progress (production/deliveries/approvals tracking)
4. Orchestration Summary (AI automated vs user needed)
5. Stock Receipt Modal scenarios
6. AI Prevented Issues showcase
7. Alert Hub with all alert types
This creates a realistic dashboard state with:
- Actions in all time groups (urgent <6h, today <24h, week <7d)
- Execution progress with on_track/at_risk states
- AI prevented issues with savings
- Deliveries ready for stock receipt
- Production batches in various states
- Purchase orders needing approval
Usage:
python services/demo_session/scripts/seed_dashboard_comprehensive.py
Environment Variables:
RABBITMQ_URL: RabbitMQ connection URL (default: amqp://guest:guest@localhost:5672/)
DEMO_TENANT_ID: Tenant ID to seed data for (default: demo-tenant-bakery-ia)
"""
import asyncio
import os
import sys
import uuid
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import List, Dict, Any
# Add project root to path
sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent))
from shared.messaging.rabbitmq import RabbitMQClient
from shared.schemas.alert_types import AlertTypeConstants
import structlog
logger = structlog.get_logger()
# Configuration
DEMO_TENANT_ID = os.getenv('DEMO_TENANT_ID', 'demo-tenant-bakery-ia')
# Build RabbitMQ URL from individual components or use direct URL
RABBITMQ_URL = os.getenv('RABBITMQ_URL')
if not RABBITMQ_URL:
rabbitmq_host = os.getenv('RABBITMQ_HOST', 'localhost')
rabbitmq_port = os.getenv('RABBITMQ_PORT', '5672')
rabbitmq_user = os.getenv('RABBITMQ_USER', 'guest')
rabbitmq_password = os.getenv('RABBITMQ_PASSWORD', 'guest')
RABBITMQ_URL = f'amqp://{rabbitmq_user}:{rabbitmq_password}@{rabbitmq_host}:{rabbitmq_port}/'
# Demo entity IDs
FLOUR_ID = "flour-tipo-55"
YEAST_ID = "yeast-fresh"
BUTTER_ID = "butter-french"
SUGAR_ID = "sugar-white"
CHOCOLATE_ID = "chocolate-dark"
CROISSANT_PRODUCT = "croissant-mantequilla"
BAGUETTE_PRODUCT = "baguette-traditional"
CHOCOLATE_CAKE_PRODUCT = "chocolate-cake"
SUPPLIER_FLOUR = "supplier-harinera"
SUPPLIER_YEAST = "supplier-levadura"
SUPPLIER_DAIRY = "supplier-lacteos"
def utc_now() -> datetime:
"""Get current UTC time"""
return datetime.now(timezone.utc)
# ============================================================
# 1. UNIFIED ACTION QUEUE - Time-Based Grouping
# ============================================================
def create_urgent_actions() -> List[Dict[str, Any]]:
"""
Create URGENT actions (<6 hours deadline)
These appear in the 🔴 URGENT section
"""
now = utc_now()
return [
# PO Approval Escalation - 2h deadline
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'procurement',
'alert_type': AlertTypeConstants.PO_APPROVAL_ESCALATION,
'title': 'URGENT: PO Approval Needed - Yeast Supplier',
'message': 'Purchase order #PO-2024-089 has been pending for 72 hours. Production batch depends on this delivery tomorrow morning.',
'alert_metadata': {
'po_id': 'po-2024-089',
'po_number': 'PO-2024-089',
'supplier_id': SUPPLIER_YEAST,
'supplier_name': 'Levadura Fresh S.L.',
'supplier_phone': '+34-555-1234',
'total_amount': 450.00,
'currency': 'EUR',
'item_categories': ['Yeast', 'Leavening Agents'],
'delivery_date': (now + timedelta(hours=10)).isoformat(),
'batch_id': 'batch-croissants-tomorrow',
'batch_name': 'Croissants Butter - Morning Batch',
'financial_impact_eur': 1200,
'orders_affected': 8,
'escalation': {
'aged_hours': 72,
'priority_boost': 20,
'reason': 'pending_over_72h'
},
'urgency_context': {
'deadline': (now + timedelta(hours=2)).isoformat(),
'time_until_consequence_hours': 2,
'auto_action_countdown_seconds': 7200, # 2h countdown
'can_wait_until_tomorrow': False
}
},
'timestamp': (now - timedelta(hours=72)).isoformat()
},
# Delivery Overdue - Needs immediate action
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'procurement',
'alert_type': AlertTypeConstants.DELIVERY_OVERDUE,
'title': 'Delivery Overdue: Flour Delivery',
'message': 'Expected delivery from Harinera San José is 4 hours overdue. Contact supplier immediately.',
'alert_metadata': {
'po_id': 'po-2024-085',
'po_number': 'PO-2024-085',
'supplier_id': SUPPLIER_FLOUR,
'supplier_name': 'Harinera San José',
'supplier_phone': '+34-555-5678',
'supplier_email': 'pedidos@harinerasj.es',
'ingredient_id': FLOUR_ID,
'ingredient_name': 'Harina Tipo 55',
'quantity_expected': 500,
'unit': 'kg',
'expected_delivery': (now - timedelta(hours=4)).isoformat(),
'hours_overdue': 4,
'stock_runout_hours': 18,
'batches_at_risk': ['batch-baguettes-001', 'batch-croissants-002'],
'urgency_context': {
'deadline': (now + timedelta(hours=3)).isoformat(),
'time_until_consequence_hours': 3,
'can_wait_until_tomorrow': False
}
},
'timestamp': (now - timedelta(hours=4)).isoformat()
},
# Production Batch At Risk - 5h window
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'production',
'alert_type': AlertTypeConstants.BATCH_AT_RISK,
'title': 'Batch At Risk: Missing Ingredients',
'message': 'Batch "Chocolate Cakes Evening" scheduled in 5 hours but missing 3kg dark chocolate.',
'alert_metadata': {
'batch_id': 'batch-chocolate-cake-evening',
'batch_name': 'Chocolate Cakes Evening',
'product_id': CHOCOLATE_CAKE_PRODUCT,
'product_name': 'Chocolate Cake Premium',
'planned_start': (now + timedelta(hours=5)).isoformat(),
'missing_ingredients': [
{'ingredient_id': CHOCOLATE_ID, 'name': 'Dark Chocolate 70%', 'needed': 3, 'available': 0, 'unit': 'kg'}
],
'orders_dependent': 5,
'financial_impact_eur': 380,
'urgency_context': {
'deadline': (now + timedelta(hours=5)).isoformat(),
'time_until_consequence_hours': 5,
'can_wait_until_tomorrow': False
}
},
'timestamp': now.isoformat()
}
]
def create_today_actions() -> List[Dict[str, Any]]:
"""
Create TODAY actions (<24 hours deadline)
These appear in the 🟡 TODAY section
"""
now = utc_now()
return [
# PO Approval Needed - Standard priority
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'procurement',
'alert_type': AlertTypeConstants.PO_APPROVAL_NEEDED,
'title': 'PO Approval: Butter & Dairy Products',
'message': 'Purchase order for weekly dairy delivery needs your approval. Delivery scheduled for Friday.',
'alert_metadata': {
'po_id': 'po-2024-090',
'po_number': 'PO-2024-090',
'supplier_id': SUPPLIER_DAIRY,
'supplier_name': 'Lácteos Frescos Madrid',
'supplier_phone': '+34-555-9012',
'total_amount': 890.50,
'currency': 'EUR',
'item_categories': ['Butter', 'Cream', 'Milk'],
'delivery_date': (now + timedelta(days=2)).isoformat(),
'line_items': [
{'ingredient': 'French Butter', 'quantity': 20, 'unit': 'kg', 'price': 12.50},
{'ingredient': 'Heavy Cream', 'quantity': 15, 'unit': 'L', 'price': 4.20},
{'ingredient': 'Whole Milk', 'quantity': 30, 'unit': 'L', 'price': 1.80}
],
'urgency_context': {
'deadline': (now + timedelta(hours=20)).isoformat(),
'time_until_consequence_hours': 20,
'can_wait_until_tomorrow': True
}
},
'timestamp': (now - timedelta(hours=6)).isoformat()
},
# Delivery Arriving Soon - Needs preparation
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'procurement',
'alert_type': AlertTypeConstants.DELIVERY_ARRIVING_SOON,
'title': 'Delivery Arriving in 8 Hours: Sugar & Ingredients',
'message': 'Prepare for incoming delivery. Stock receipt will be required.',
'alert_metadata': {
'po_id': 'po-2024-088',
'po_number': 'PO-2024-088',
'supplier_id': 'supplier-ingredients',
'supplier_name': 'Ingredientes Premium',
'supplier_phone': '+34-555-3456',
'delivery_id': 'delivery-2024-088',
'expected_arrival': (now + timedelta(hours=8)).isoformat(),
'item_count': 5,
'total_weight_kg': 250,
'requires_stock_receipt': True,
'warehouse_location': 'Warehouse A - Section 3',
'line_items': [
{'ingredient': 'White Sugar', 'quantity': 100, 'unit': 'kg'},
{'ingredient': 'Brown Sugar', 'quantity': 50, 'unit': 'kg'},
{'ingredient': 'Vanilla Extract', 'quantity': 2, 'unit': 'L'}
],
'urgency_context': {
'deadline': (now + timedelta(hours=8)).isoformat(),
'time_until_consequence_hours': 8,
'can_wait_until_tomorrow': False
}
},
'timestamp': now.isoformat()
},
# Low Stock Warning - Today action recommended
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'inventory',
'alert_type': AlertTypeConstants.LOW_STOCK_WARNING,
'title': 'Low Stock: Fresh Yeast',
'message': 'Fresh yeast stock is low. Current: 2.5kg, Minimum: 10kg. Recommend ordering today.',
'alert_metadata': {
'ingredient_id': YEAST_ID,
'ingredient_name': 'Fresh Yeast',
'current_stock': 2.5,
'minimum_stock': 10,
'maximum_stock': 25,
'unit': 'kg',
'daily_consumption_avg': 3.5,
'days_remaining': 0.7,
'supplier_name': 'Levadura Fresh S.L.',
'last_order_date': (now - timedelta(days=8)).isoformat(),
'recommended_order_quantity': 20,
'urgency_context': {
'stockout_risk_hours': 17,
'can_wait_until_tomorrow': True
}
},
'timestamp': (now - timedelta(hours=3)).isoformat()
}
]
def create_week_actions() -> List[Dict[str, Any]]:
"""
Create WEEK actions (<7 days deadline)
These appear in the 🟢 THIS WEEK section
"""
now = utc_now()
return [
# Demand Surge Predicted - Plan ahead
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'forecasting',
'alert_type': AlertTypeConstants.DEMAND_SURGE_PREDICTED,
'title': 'Weekend Demand Surge Predicted',
'message': 'Sunny weather forecast for Saturday-Sunday. Expect 25% demand increase for croissants and pastries.',
'alert_metadata': {
'forecast_type': 'weather_based',
'weather_condition': 'sunny',
'days_affected': [
(now + timedelta(days=3)).date().isoformat(),
(now + timedelta(days=4)).date().isoformat()
],
'expected_demand_increase_pct': 25,
'products_affected': [
{'product_id': CROISSANT_PRODUCT, 'product_name': 'Croissant Butter', 'increase_pct': 30},
{'product_id': BAGUETTE_PRODUCT, 'product_name': 'Baguette Traditional', 'increase_pct': 20}
],
'confidence': 0.85,
'recommended_action': 'Increase production by 25% and ensure adequate stock',
'estimated_revenue_opportunity_eur': 450,
'urgency_context': {
'deadline': (now + timedelta(days=2)).isoformat(),
'can_wait_until_tomorrow': True
}
},
'timestamp': now.isoformat()
},
# Stock Receipt Incomplete - Can wait
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'inventory',
'alert_type': AlertTypeConstants.STOCK_RECEIPT_INCOMPLETE,
'title': 'Stock Receipt Pending: Flour Delivery',
'message': 'Delivery received 2 days ago but stock receipt not completed. Please confirm lot details and expiration dates.',
'alert_metadata': {
'receipt_id': 'receipt-2024-012',
'po_id': 'po-2024-083',
'po_number': 'PO-2024-083',
'supplier_name': 'Harinera San José',
'delivery_date': (now - timedelta(days=2)).isoformat(),
'days_since_delivery': 2,
'line_items_pending': 3,
'total_items': 3,
'requires_lot_tracking': True,
'requires_expiration': True,
'urgency_context': {
'deadline': (now + timedelta(days=5)).isoformat(),
'can_wait_until_tomorrow': True
}
},
'timestamp': (now - timedelta(days=2)).isoformat()
}
]
# ============================================================
# 2. AI PREVENTED ISSUES - Showcase AI Value
# ============================================================
def create_prevented_issues() -> List[Dict[str, Any]]:
"""
Create alerts showing AI prevented issues (type_class: prevented_issue)
These show in the Health Status Card and Prevented Issues Card
"""
now = utc_now()
return [
# Prevented Stockout - PO created automatically
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'inventory',
'alert_type': 'ai_prevented_stockout',
'title': '✅ AI Prevented Stockout: Flour',
'message': 'AI detected upcoming stockout and created purchase order automatically. Delivery arriving Friday.',
'alert_metadata': {
'type_class': 'prevented_issue',
'priority_level': 'info',
'ingredient_id': FLOUR_ID,
'ingredient_name': 'Harina Tipo 55',
'prevented_risk': 'stockout',
'ai_action_taken': 'purchase_order_created',
'po_id': 'po-2024-091',
'po_number': 'PO-2024-091',
'quantity_ordered': 500,
'unit': 'kg',
'supplier_name': 'Harinera San José',
'delivery_date': (now + timedelta(days=2)).isoformat(),
'estimated_savings_eur': 250,
'orchestrator_context': {
'already_addressed': True,
'action_type': 'purchase_order',
'action_id': 'po-2024-091',
'action_status': 'pending_approval',
'reasoning': 'Detected stock would run out in 1.8 days based on historical consumption patterns'
},
'business_impact': {
'prevented_stockout_hours': 43,
'affected_orders_prevented': 12,
'production_batches_secured': 4
},
'ai_reasoning_summary': 'Analyzed consumption patterns and detected stockout in 43 hours. Created PO for 500kg to arrive Friday, preventing disruption to 4 production batches.'
},
'timestamp': (now - timedelta(hours=12)).isoformat()
},
# Prevented Waste - Production adjusted
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'production',
'alert_type': 'ai_prevented_waste',
'title': '✅ AI Prevented Waste: Reduced Monday Production',
'message': 'AI detected post-weekend demand pattern and reduced Monday production by 15%, preventing €120 in waste.',
'alert_metadata': {
'type_class': 'prevented_issue',
'priority_level': 'info',
'product_id': BAGUETTE_PRODUCT,
'product_name': 'Baguette Traditional',
'prevented_risk': 'waste',
'ai_action_taken': 'production_adjusted',
'reduction_pct': 15,
'units_reduced': 45,
'day_of_week': 'Monday',
'historical_pattern': 'post_weekend_low_demand',
'estimated_savings_eur': 120,
'orchestrator_context': {
'already_addressed': True,
'action_type': 'production_batch',
'action_id': 'batch-baguettes-monday-adjusted',
'action_status': 'completed',
'reasoning': 'Historical data shows 18% demand drop on Mondays following sunny weekends'
},
'business_impact': {
'waste_prevented_kg': 12,
'waste_reduction_pct': 15
},
'ai_reasoning_summary': 'Detected consistent Monday demand drop (18% avg) in post-weekend data. Adjusted production to prevent overproduction and waste.'
},
'timestamp': (now - timedelta(days=1)).isoformat()
},
# Prevented Production Delay - Batch rescheduled
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'production',
'alert_type': 'ai_prevented_delay',
'title': '✅ AI Prevented Delay: Rescheduled Conflicting Batches',
'message': 'AI detected oven capacity conflict and rescheduled batches to optimize throughput.',
'alert_metadata': {
'type_class': 'prevented_issue',
'priority_level': 'info',
'prevented_risk': 'production_delay',
'ai_action_taken': 'batch_rescheduled',
'batches_affected': 3,
'equipment_id': 'oven-001',
'equipment_name': 'Industrial Oven #1',
'capacity_utilization_before': 110,
'capacity_utilization_after': 95,
'time_saved_minutes': 45,
'estimated_savings_eur': 85,
'orchestrator_context': {
'already_addressed': True,
'action_type': 'batch_optimization',
'action_status': 'completed',
'reasoning': 'Detected overlapping batch schedules would exceed oven capacity by 10%'
},
'business_impact': {
'orders_on_time': 8,
'customer_satisfaction_impact': 'high'
},
'ai_reasoning_summary': 'Identified capacity conflict in oven schedule. Rescheduled 3 batches to maintain on-time delivery for 8 orders.'
},
'timestamp': (now - timedelta(hours=18)).isoformat()
}
]
# ============================================================
# 3. EXECUTION PROGRESS - Production/Deliveries/Approvals
# ============================================================
def create_production_batches() -> List[Dict[str, Any]]:
"""
Create production batch data for execution progress tracking
"""
now = utc_now()
return [
# Completed batch
{
'batch_id': 'batch-morning-croissants',
'product_name': 'Croissant Butter',
'quantity': 120,
'status': 'completed',
'planned_start': (now - timedelta(hours=4)).isoformat(),
'actual_start': (now - timedelta(hours=4, minutes=5)).isoformat(),
'actual_end': (now - timedelta(hours=1)).isoformat()
},
# In progress batch
{
'batch_id': 'batch-baguettes-lunch',
'product_name': 'Baguette Traditional',
'quantity': 80,
'status': 'in_progress',
'planned_start': (now - timedelta(hours=2)).isoformat(),
'actual_start': (now - timedelta(hours=2, minutes=10)).isoformat(),
'progress_pct': 65
},
# Pending batches
{
'batch_id': 'batch-afternoon-pastries',
'product_name': 'Mixed Pastries',
'quantity': 50,
'status': 'pending',
'planned_start': (now + timedelta(hours=1)).isoformat()
},
{
'batch_id': 'batch-evening-bread',
'product_name': 'Artisan Bread Assortment',
'quantity': 40,
'status': 'pending',
'planned_start': (now + timedelta(hours=3)).isoformat()
}
]
# ============================================================
# MAIN SEEDING FUNCTION
# ============================================================
async def seed_comprehensive_dashboard():
"""
Seed comprehensive dashboard demo data
Creates realistic dashboard state showcasing:
- All time-based action groups (urgent/today/week)
- AI prevented issues with savings
- Execution progress tracking
- Stock receipt scenarios
- Full alert type coverage
"""
print("\n" + "="*80)
print("🚀 SEEDING COMPREHENSIVE DASHBOARD DEMO DATA")
print("="*80 + "\n")
print(f"📋 Configuration:")
print(f" Tenant ID: {DEMO_TENANT_ID}")
print(f" RabbitMQ: {RABBITMQ_URL}")
print()
try:
# Initialize RabbitMQ
logger.info("Connecting to RabbitMQ", url=RABBITMQ_URL)
rabbitmq_client = RabbitMQClient(RABBITMQ_URL, 'dashboard-demo-seeder')
await rabbitmq_client.connect()
# Collect all alerts
all_alerts = []
all_alerts.extend(create_urgent_actions())
all_alerts.extend(create_today_actions())
all_alerts.extend(create_week_actions())
all_alerts.extend(create_prevented_issues())
print(f"📊 Dashboard Scenarios to Seed:")
print(f" 🔴 URGENT actions (<6h): {len(create_urgent_actions())}")
print(f" 🟡 TODAY actions (<24h): {len(create_today_actions())}")
print(f" 🟢 WEEK actions (<7d): {len(create_week_actions())}")
print(f" ✅ AI Prevented Issues: {len(create_prevented_issues())}")
print(f" 📦 Total Alerts: {len(all_alerts)}")
print()
# Publish alerts
print("📤 Publishing Alerts:")
print("-" * 80)
success_count = 0
for i, alert in enumerate(all_alerts, 1):
routing_key = f"{alert['item_type']}.{alert['service']}.{alert['alert_type']}"
success = await rabbitmq_client.publish_event(
exchange_name='alerts.exchange',
routing_key=routing_key,
event_data=alert,
persistent=True
)
if success:
success_count += 1
status = "✅"
else:
status = "❌"
logger.warning("Failed to publish alert", alert_id=alert['id'])
# Determine time group emoji
if 'escalation' in alert.get('alert_metadata', {}) or \
alert.get('alert_metadata', {}).get('urgency_context', {}).get('time_until_consequence_hours', 999) < 6:
group = "🔴 URGENT"
elif alert.get('alert_metadata', {}).get('urgency_context', {}).get('time_until_consequence_hours', 999) < 24:
group = "🟡 TODAY"
elif alert.get('alert_metadata', {}).get('type_class') == 'prevented_issue':
group = "✅ PREVENTED"
else:
group = "🟢 WEEK"
print(f" {i:2d}. {status} [{group}] {alert['title']}")
print()
print(f"✅ Published {success_count}/{len(all_alerts)} alerts successfully")
print()
await rabbitmq_client.disconnect()
# Print dashboard preview
print("="*80)
print("📊 EXPECTED DASHBOARD STATE")
print("="*80)
print()
print("🏥 HEALTH STATUS:")
print(" Status: YELLOW (actions needed)")
print(" Checklist:")
print(" ⚡ AI Handled: 3 issues prevented (€455 saved)")
print(" ⚠️ Needs You: 3 urgent actions, 3 today actions")
print()
print("📋 ACTION QUEUE:")
print(" 🔴 URGENT (<6h): 3 actions")
print(" - PO Approval Escalation (2h deadline)")
print(" - Delivery Overdue (4h late)")
print(" - Batch At Risk (5h until start)")
print()
print(" 🟡 TODAY (<24h): 3 actions")
print(" - PO Approval: Dairy Products")
print(" - Delivery Arriving Soon (8h)")
print(" - Low Stock: Fresh Yeast")
print()
print(" 🟢 THIS WEEK (<7d): 2 actions")
print(" - Weekend Demand Surge")
print(" - Stock Receipt Incomplete")
print()
print("📊 EXECUTION PROGRESS:")
print(" Production: 2/4 batches (on_track)")
print(" ✅ Completed: 1")
print(" 🔄 In Progress: 1")
print(" ⏳ Pending: 2")
print()
print(" Deliveries: Status depends on real PO data")
print(" Approvals: 2 pending")
print()
print("✅ AI PREVENTED ISSUES:")
print(" Total Prevented: 3 issues")
print(" Total Savings: €455")
print(" Details:")
print(" - Prevented stockout (€250 saved)")
print(" - Prevented waste (€120 saved)")
print(" - Prevented delay (€85 saved)")
print()
print("="*80)
print("🎉 DASHBOARD DEMO SEEDED SUCCESSFULLY!")
print("="*80)
print()
print("Next Steps:")
print(" 1. Verify alert-processor is running:")
print(" kubectl get pods -l app.kubernetes.io/name=alert-processor-service")
print()
print(" 2. Check alert enrichment logs:")
print(" kubectl logs -f deployment/alert-processor-service | grep 'enriched_alert'")
print()
print(" 3. View dashboard:")
print(" http://localhost:3000/dashboard")
print()
print(" 4. Test smart actions:")
print(" - Approve/Reject PO from action queue")
print(" - Mark delivery as received (opens stock receipt modal)")
print(" - Call supplier (initiates phone call)")
print(" - Adjust production (navigates to production page)")
print()
except Exception as e:
logger.error("Failed to seed dashboard demo", error=str(e), exc_info=True)
print(f"\n❌ ERROR: {str(e)}")
print("\nTroubleshooting:")
print(" • Verify RabbitMQ is running: kubectl get pods | grep rabbitmq")
print(" • Check RABBITMQ_URL environment variable")
print(" • Ensure alerts.exchange exists")
print(" • Check alert-processor service logs for errors")
raise
if __name__ == "__main__":
# Load environment variables
from dotenv import load_dotenv
load_dotenv()
# Run seeder
asyncio.run(seed_comprehensive_dashboard())

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services/demo_session/scripts/seed_enriched_alert_demo.py Normal file
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#!/usr/bin/env python3
"""
Seed demo data for Unified Alert Service
This script creates demo alerts that showcase the enrichment capabilities:
- Low stock (AI already handled - prevented issue)
- Supplier delay (action needed - critical)
- Waste trend (trend warning - standard)
- Orchestrator actions (for context enrichment)
The unified alert-processor service automatically enriches all alerts with:
- Multi-factor priority scoring
- Orchestrator context (AI actions)
- Business impact analysis
- Smart actions with deep links
- Timing intelligence
Usage:
python services/demo_session/scripts/seed_enriched_alert_demo.py
"""
import asyncio
import os
import sys
import uuid
from datetime import datetime, timedelta
from pathlib import Path
# Add project root to path
sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent))
from shared.messaging.rabbitmq import RabbitMQClient
import structlog
logger = structlog.get_logger()
# Demo tenant ID (should match existing demo tenant)
DEMO_TENANT_ID = "demo-tenant-bakery-ia"
# Demo entity IDs (should match existing demo data)
FLOUR_INGREDIENT_ID = "flour-tipo-55"
YEAST_INGREDIENT_ID = "yeast-fresh"
CROISSANT_PRODUCT_ID = "croissant-mantequilla"
CROISSANT_BATCH_ID = "batch-croissants-001"
YEAST_SUPPLIER_ID = "supplier-levadura-fresh"
FLOUR_PO_ID = "po-flour-demo-001"
# Demo alerts for unified alert-processor (automatically enriched)
DEMO_ALERTS = [
# Alert 1: Low Stock - AI Already Handled (Prevented Issue)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'inventory',
'type': 'low_stock',
'severity': 'warning', # Will be enriched with priority score ~71
'title': 'Bajo Stock: Harina Tipo 55',
'message': 'Stock: 45kg, Mínimo: 200kg',
'actions': [], # Will be enhanced with smart actions
'metadata': {
'ingredient_id': FLOUR_INGREDIENT_ID,
'ingredient_name': 'Harina Tipo 55',
'current_stock': 45,
'minimum_stock': 200,
'unit': 'kg',
'supplier_name': 'Harinera San José',
'last_order_date': (datetime.utcnow() - timedelta(days=7)).isoformat()
},
'timestamp': datetime.utcnow().isoformat()
},
# Alert 2: Supplier Delay - Action Needed (Critical)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'procurement',
'type': 'supplier_delay',
'severity': 'critical', # Will be enriched with priority score ~92
'actions': [], # Will be enhanced with smart actions
'title': 'Retraso de Proveedor: Levadura Fresh',
'message': 'Entrega retrasada 24 horas. Levadura necesaria para producción de mañana.',
'metadata': {
'supplier_id': YEAST_SUPPLIER_ID,
'supplier_name': 'Levadura Fresh',
'supplier_phone': '+34-555-1234',
'supplier_email': 'pedidos@levadura-fresh.es',
'ingredient_id': YEAST_INGREDIENT_ID,
'ingredient_name': 'Levadura Fresca',
'batch_id': CROISSANT_BATCH_ID,
'batch_name': 'Croissants Mantequilla Mañana',
'orders_affected': 3,
'financial_impact_eur': 450,
'deadline': (datetime.utcnow() + timedelta(hours=6)).isoformat(),
'quantity_needed': 15,
'unit': 'kg'
},
'timestamp': datetime.utcnow().isoformat()
},
# Alert 3: Waste Trend - Trend Warning (Standard)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'production',
'type': 'waste_trend',
'severity': 'medium', # Will be enriched with priority score ~58
'actions': [], # Will be enhanced with smart actions
'title': 'Tendencia de Desperdicio: Croissants',
'message': 'Desperdicio aumentó 15% en 3 días. Patrón detectado: sobreproducción miércoles.',
'metadata': {
'product_id': CROISSANT_PRODUCT_ID,
'product_name': 'Croissant Mantequilla',
'waste_percentage': 23,
'baseline_percentage': 8,
'trend_days': 3,
'pattern': 'wednesday_overproduction',
'pattern_description': 'Desperdicio consistentemente alto los miércoles (18%, 21%, 23%)',
'financial_impact_eur': 180,
'recommendation': 'Reducir producción miércoles en 25 unidades',
'confidence': 0.85,
'historical_data': [
{'day': 'Mon', 'waste_pct': 7},
{'day': 'Tue', 'waste_pct': 9},
{'day': 'Wed', 'waste_pct': 23},
{'day': 'Thu', 'waste_pct': 8},
{'day': 'Fri', 'waste_pct': 6}
]
},
'timestamp': datetime.utcnow().isoformat()
},
# Alert 4: Forecast Anomaly - Information (Low Priority)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'forecasting',
'type': 'forecast_updated',
'severity': 'low', # Will be enriched with priority score ~35
'actions': [], # Will be enhanced with smart actions
'title': 'Previsión Actualizada: Fin de Semana Soleado',
'message': 'Pronóstico meteorológico actualizado: soleado sábado y domingo. Aumento de demanda esperado.',
'metadata': {
'forecast_type': 'weather_based',
'weather_condition': 'sunny',
'days_affected': ['2024-11-23', '2024-11-24'],
'expected_demand_increase_pct': 15,
'confidence': 0.78,
'recommended_action': 'Aumentar producción croissants y pan rústico 15%'
},
'timestamp': datetime.utcnow().isoformat()
},
# Alert 5: Equipment Maintenance - Action Needed (Medium)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'item_type': 'alert',
'service': 'production',
'type': 'equipment_maintenance',
'severity': 'medium', # Will be enriched with priority score ~65
'actions': [], # Will be enhanced with smart actions
'title': 'Mantenimiento Programado: Horno Industrial',
'message': 'Horno principal requiere mantenimiento en 48 horas según calendario.',
'metadata': {
'equipment_id': 'oven-001',
'equipment_name': 'Horno Industrial Principal',
'equipment_type': 'oven',
'maintenance_type': 'preventive',
'scheduled_date': (datetime.utcnow() + timedelta(hours=48)).isoformat(),
'estimated_duration_hours': 3,
'last_maintenance': (datetime.utcnow() - timedelta(days=90)).isoformat(),
'maintenance_interval_days': 90,
'supplier_contact': 'TecnoHornos Madrid',
'supplier_phone': '+34-555-6789'
},
'timestamp': datetime.utcnow().isoformat()
}
]
# Demo orchestrator actions (for context enrichment)
DEMO_ORCHESTRATOR_ACTIONS = [
# Action 1: PO Created for Flour (provides context for Alert 1)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'action_type': 'purchase_order_created',
'reasoning_type': 'preventive',
'entity_type': 'purchase_order',
'entity_id': FLOUR_PO_ID,
'summary': 'Pedido de compra #12345 creado para 500kg harina',
'reasoning_summary': 'Detecté que el stock se agotará en 2.3 días basándome en patrones históricos de demanda. Creé pedido de compra para llegar el viernes.',
'metadata': {
'ingredient_id': FLOUR_INGREDIENT_ID,
'ingredient_name': 'Harina Tipo 55',
'quantity': 500,
'unit': 'kg',
'supplier_name': 'Harinera San José',
'po_number': 'PO-12345',
'estimated_delivery': (datetime.utcnow() + timedelta(days=2, hours=10)).isoformat(),
'estimated_savings_eur': 200,
'prevented_issue': 'stockout',
'confidence': 0.92,
'demand_forecast_method': 'historical_patterns',
'stock_runout_days': 2.3
},
'created_at': (datetime.utcnow() - timedelta(hours=2)).isoformat()
},
# Action 2: Batch Scheduled for Weekend (weather-based)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'action_type': 'batch_scheduled',
'reasoning_type': 'weather_based',
'entity_type': 'production_batch',
'entity_id': CROISSANT_BATCH_ID,
'summary': 'Aumentada producción croissants 20% para sábado',
'reasoning_summary': 'Pronóstico meteorológico muestra fin de semana soleado. Datos históricos muestran aumento de demanda 15% en sábados soleados.',
'metadata': {
'product_id': CROISSANT_PRODUCT_ID,
'product_name': 'Croissant Mantequilla',
'quantity_increase': 25,
'quantity_increase_pct': 20,
'date': (datetime.utcnow() + timedelta(days=2)).date().isoformat(),
'weather_condition': 'sunny',
'confidence': 0.85,
'historical_sunny_saturday_demand_increase': 15,
'estimated_additional_revenue_eur': 180
},
'created_at': (datetime.utcnow() - timedelta(hours=4)).isoformat()
},
# Action 3: Waste Reduction Adjustment (for trend context)
{
'id': str(uuid.uuid4()),
'tenant_id': DEMO_TENANT_ID,
'action_type': 'production_adjusted',
'reasoning_type': 'waste_reduction',
'entity_type': 'production_plan',
'entity_id': str(uuid.uuid4()),
'summary': 'Reducida producción lunes 10% basado en patrón post-fin de semana',
'reasoning_summary': 'Detecté patrón de baja demanda post-fin de semana. Histórico muestra reducción 12% demanda lunes. Ajusté producción para prevenir desperdicio.',
'metadata': {
'day_of_week': 'monday',
'reduction_pct': 10,
'historical_demand_drop_pct': 12,
'products_affected': ['Croissant Mantequilla', 'Pan Rústico'],
'estimated_waste_prevented_eur': 85,
'confidence': 0.78
},
'created_at': (datetime.utcnow() - timedelta(hours=20)).isoformat()
}
]
async def seed_enriched_alert_demo():
"""
Seed demo data for unified alert service
This creates alerts that will be automatically enriched by alert-processor with:
- Multi-factor priority scoring
- Orchestrator context (AI actions)
- Business impact analysis
- Smart actions
- Timing intelligence
"""
print("\n" + "="*70)
print("🚀 SEEDING DEMO DATA FOR UNIFIED ALERT SERVICE")
print("="*70 + "\n")
rabbitmq_url = os.getenv('RABBITMQ_URL', 'amqp://guest:guest@localhost:5672/')
try:
# Initialize RabbitMQ client
logger.info("Connecting to RabbitMQ", url=rabbitmq_url)
rabbitmq_client = RabbitMQClient(rabbitmq_url, 'demo-seeder')
await rabbitmq_client.connect()
# Publish demo alerts (will be automatically enriched)
print("\n📤 Publishing Alerts (Automatic Enrichment):")
print("-" * 70)
for i, alert in enumerate(DEMO_ALERTS, 1):
routing_key = f"{alert['item_type']}.{alert['service']}.{alert['type']}"
# Use publish_event method (correct API)
success = await rabbitmq_client.publish_event(
exchange_name='alerts.exchange',
routing_key=routing_key,
event_data=alert,
persistent=True
)
if not success:
logger.warning("Failed to publish alert", alert_id=alert['id'])
continue
print(f" {i}. ✅ {alert['title']}")
print(f" Service: {alert['service']}")
print(f" Severity: {alert['severity']} (will be enriched)")
print(f" Routing Key: {routing_key}")
print()
# Note about orchestrator actions
print("\n📊 Orchestrator Actions (for Context Enrichment):")
print("-" * 70)
print("NOTE: Orchestrator actions should be seeded via orchestrator service.")
print("These provide context for 'AI already handled' enrichment.\n")
for i, action in enumerate(DEMO_ORCHESTRATOR_ACTIONS, 1):
print(f" {i}. {action['summary']}")
print(f" Type: {action['reasoning_type']}")
print(f" Created: {action['created_at']}")
print()
print("💡 TIP: To seed orchestrator actions, run:")
print(" python services/orchestrator/scripts/seed_demo_actions.py")
print()
await rabbitmq_client.disconnect()
print("="*70)
print("✅ DEMO ALERTS SEEDED SUCCESSFULLY!")
print("="*70)
print()
print("Next steps:")
print(" 1. Verify alert-processor service is running:")
print(" kubectl get pods -l app.kubernetes.io/name=alert-processor-service")
print()
print(" 2. Check logs for automatic enrichment:")
print(" kubectl logs -f deployment/alert-processor-service")
print()
print(" 3. View enriched alerts in dashboard:")
print(" http://localhost:3000/dashboard")
print()
print("Expected automatic enrichment:")
print(" • Low Stock Alert → Important (71) - Prevented Issue + Smart Actions")
print(" • Supplier Delay → Critical (92) - Action Needed + Deep Links")
print(" • Waste Trend → Standard (58) - Trend Warning + AI Reasoning")
print(" • Forecast Update → Info (35) - Information")
print(" • Equipment Maint → Standard (65) - Action Needed + Timing")
print()
print("All alerts enriched with:")
print(" ✓ Multi-factor priority scores")
print(" ✓ Orchestrator context (AI actions)")
print(" ✓ Business impact analysis")
print(" ✓ Smart actions with deep links")
print(" ✓ Timing intelligence")
print()
except Exception as e:
logger.error("Failed to seed demo data", error=str(e))
print(f"\n❌ ERROR: {str(e)}")
print("\nTroubleshooting:")
print(" • Verify RabbitMQ is running: kubectl get pods | grep rabbitmq")
print(" • Check RABBITMQ_URL environment variable")
print(" • Ensure raw_alerts exchange can be created")
raise
if __name__ == "__main__":
# Load environment variables
from dotenv import load_dotenv
load_dotenv()
# Run seeder
asyncio.run(seed_enriched_alert_demo())