demo seed change 7
This commit is contained in:
Urtzi Alfaro
@@ -388,6 +388,7 @@ async def clone_demo_data(
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quality_score=batch_data.get('quality_score'),
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waste_quantity=batch_data.get('waste_quantity'),
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defect_quantity=batch_data.get('defect_quantity'),
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waste_defect_type=batch_data.get('waste_defect_type'),
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equipment_used=batch_data.get('equipment_used'),
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staff_assigned=batch_data.get('staff_assigned'),
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station_id=batch_data.get('station_id'),
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@@ -395,6 +396,7 @@ async def clone_demo_data(
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forecast_id=batch_data.get('forecast_id'),
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is_rush_order=batch_data.get('is_rush_order', False),
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is_special_recipe=batch_data.get('is_special_recipe', False),
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is_ai_assisted=batch_data.get('is_ai_assisted', False),
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production_notes=batch_data.get('production_notes'),
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quality_notes=batch_data.get('quality_notes'),
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delay_reason=batch_data.get('delay_reason'),
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293
services/production/app/api/sustainability.py
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293
services/production/app/api/sustainability.py
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@@ -0,0 +1,293 @@
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"""
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Production Service - Sustainability API
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Exposes production-specific sustainability metrics following microservices principles
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Each service owns its domain data
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"""
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from datetime import datetime, timedelta
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from typing import Optional
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from uuid import UUID
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from fastapi import APIRouter, Depends, Path, Query, Request
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import structlog
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from shared.auth.decorators import get_current_user_dep
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from app.services.production_service import ProductionService
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from shared.routing import RouteBuilder
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logger = structlog.get_logger()
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# Create route builder for consistent URL structure
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route_builder = RouteBuilder('production')
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router = APIRouter(tags=["production-sustainability"])
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def get_production_service(request: Request) -> ProductionService:
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"""Dependency injection for production service"""
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from app.core.database import database_manager
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from app.core.config import settings
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notification_service = getattr(request.app.state, 'notification_service', None)
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return ProductionService(database_manager, settings, notification_service)
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@router.get(
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"/api/v1/tenants/{tenant_id}/production/sustainability/waste-metrics",
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response_model=dict,
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summary="Get production waste metrics",
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description="""
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Returns production-specific waste metrics for sustainability tracking.
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This endpoint is part of the microservices architecture where each service
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owns its domain data. Frontend aggregates data from multiple services.
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Metrics include:
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- Total production waste from batches (waste_quantity + defect_quantity)
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- Production volumes (planned vs actual)
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- Waste breakdown by defect type
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- AI-assisted batch tracking
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"""
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)
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async def get_production_waste_metrics(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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start_date: Optional[datetime] = Query(None, description="Start date for metrics (default: 30 days ago)"),
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end_date: Optional[datetime] = Query(None, description="End date for metrics (default: now)"),
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current_user: dict = Depends(get_current_user_dep),
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production_service: ProductionService = Depends(get_production_service)
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):
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"""
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Get production waste metrics for sustainability dashboard
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Returns production-specific metrics that frontend will aggregate with
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inventory metrics for complete sustainability picture.
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"""
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try:
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# Set default dates
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if not end_date:
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end_date = datetime.now()
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if not start_date:
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start_date = end_date - timedelta(days=30)
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# Get waste analytics from production service
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waste_data = await production_service.get_waste_analytics(
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tenant_id=tenant_id,
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start_date=start_date,
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end_date=end_date
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)
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# Enrich with metadata
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response = {
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**waste_data,
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"service": "production",
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"period": {
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"start_date": start_date.isoformat(),
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"end_date": end_date.isoformat(),
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"days": (end_date - start_date).days
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},
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"metadata": {
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"data_source": "production_batches",
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"calculation_method": "SUM(waste_quantity + defect_quantity)",
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"filters_applied": {
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"status": ["COMPLETED", "QUALITY_CHECK"],
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"date_range": f"{start_date.date()} to {end_date.date()}"
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}
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}
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}
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logger.info(
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"Production waste metrics retrieved",
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tenant_id=str(tenant_id),
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total_waste_kg=waste_data.get('total_production_waste', 0),
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period_days=(end_date - start_date).days,
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user_id=current_user.get('user_id')
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)
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return response
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except Exception as e:
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logger.error(
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"Error getting production waste metrics",
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tenant_id=str(tenant_id),
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error=str(e)
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)
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raise
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@router.get(
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"/api/v1/tenants/{tenant_id}/production/sustainability/baseline",
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response_model=dict,
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summary="Get production baseline metrics",
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description="""
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Returns baseline production metrics from the first 90 days of operation.
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Used by frontend to calculate SDG 12.3 compliance (waste reduction targets).
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If tenant has less than 90 days of data, returns industry average baseline.
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"""
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)
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async def get_production_baseline(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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current_user: dict = Depends(get_current_user_dep),
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production_service: ProductionService = Depends(get_production_service)
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):
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"""
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Get baseline production metrics for SDG compliance calculations
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Frontend uses this to calculate:
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- Waste reduction percentage vs baseline
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- Progress toward SDG 12.3 targets
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- Grant eligibility based on improvement
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"""
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try:
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baseline_data = await production_service.get_baseline_metrics(tenant_id)
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# Add metadata
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response = {
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**baseline_data,
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"service": "production",
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"metadata": {
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"baseline_period_days": 90,
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"calculation_method": "First 90 days of production data",
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"fallback": "Industry average (25%) if insufficient data"
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}
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}
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logger.info(
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"Production baseline metrics retrieved",
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tenant_id=str(tenant_id),
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has_baseline=baseline_data.get('has_baseline', False),
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baseline_waste_pct=baseline_data.get('waste_percentage'),
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user_id=current_user.get('user_id')
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)
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return response
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except Exception as e:
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logger.error(
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"Error getting production baseline",
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tenant_id=str(tenant_id),
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error=str(e)
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)
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raise
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@router.get(
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"/api/v1/tenants/{tenant_id}/production/sustainability/ai-impact",
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response_model=dict,
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summary="Get AI waste reduction impact",
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description="""
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Analyzes the impact of AI-assisted production on waste reduction.
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Compares waste rates between:
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- AI-assisted batches (with is_ai_assisted=true)
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- Manual batches (is_ai_assisted=false)
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Shows ROI of AI features for sustainability.
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"""
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)
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async def get_ai_waste_impact(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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start_date: Optional[datetime] = Query(None, description="Start date (default: 30 days ago)"),
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end_date: Optional[datetime] = Query(None, description="End date (default: now)"),
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current_user: dict = Depends(get_current_user_dep),
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production_service: ProductionService = Depends(get_production_service)
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):
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"""
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Get AI impact on waste reduction
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Frontend uses this to showcase:
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- Value proposition of AI features
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- Waste avoided through AI assistance
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- Financial ROI of AI investment
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"""
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try:
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# Set default dates
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if not end_date:
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end_date = datetime.now()
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if not start_date:
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start_date = end_date - timedelta(days=30)
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# Get AI impact analytics (we'll implement this)
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ai_impact = await production_service.get_ai_waste_impact(
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tenant_id=tenant_id,
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start_date=start_date,
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end_date=end_date
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)
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logger.info(
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"AI waste impact retrieved",
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tenant_id=str(tenant_id),
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ai_waste_reduction_pct=ai_impact.get('waste_reduction_percentage'),
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user_id=current_user.get('user_id')
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)
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return ai_impact
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except Exception as e:
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logger.error(
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"Error getting AI waste impact",
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tenant_id=str(tenant_id),
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error=str(e)
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)
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raise
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@router.get(
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"/api/v1/tenants/{tenant_id}/production/sustainability/summary",
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response_model=dict,
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summary="Get production sustainability summary",
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description="""
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Quick summary endpoint combining all production sustainability metrics.
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Useful for dashboard widgets that need overview data without multiple calls.
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"""
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)
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async def get_production_sustainability_summary(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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days: int = Query(30, ge=7, le=365, description="Number of days to analyze"),
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current_user: dict = Depends(get_current_user_dep),
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production_service: ProductionService = Depends(get_production_service)
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):
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"""
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Get comprehensive production sustainability summary
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Combines waste metrics, baseline, and AI impact in one response.
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Optimized for dashboard widgets.
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"""
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try:
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end_date = datetime.now()
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start_date = end_date - timedelta(days=days)
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# Get all metrics in parallel (within service)
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waste_data = await production_service.get_waste_analytics(tenant_id, start_date, end_date)
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baseline_data = await production_service.get_baseline_metrics(tenant_id)
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# Try to get AI impact (may not be available for all tenants)
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try:
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ai_impact = await production_service.get_ai_waste_impact(tenant_id, start_date, end_date)
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except:
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ai_impact = {"available": False}
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summary = {
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"service": "production",
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"period_days": days,
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"waste_metrics": waste_data,
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"baseline": baseline_data,
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"ai_impact": ai_impact,
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"last_updated": datetime.now().isoformat()
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}
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logger.info(
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"Production sustainability summary retrieved",
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tenant_id=str(tenant_id),
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period_days=days,
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user_id=current_user.get('user_id')
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)
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return summary
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except Exception as e:
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logger.error(
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"Error getting production sustainability summary",
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tenant_id=str(tenant_id),
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error=str(e)
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)
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raise
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@@ -30,7 +30,8 @@ from app.api import (
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production_orders_operations, # Tenant deletion endpoints
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audit,
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ml_insights, # ML insights endpoint
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batch
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batch,
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sustainability # Sustainability metrics endpoints
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)
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from app.api.internal_alert_trigger import router as internal_alert_trigger_router
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@@ -214,6 +215,7 @@ service.add_router(production_schedules.router)
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service.add_router(production_operations.router)
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service.add_router(production_dashboard.router)
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service.add_router(analytics.router)
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service.add_router(sustainability.router) # Sustainability metrics endpoints
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service.add_router(internal_demo.router, tags=["internal-demo"])
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service.add_router(ml_insights.router) # ML insights endpoint
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service.add_router(ml_insights.internal_router) # Internal ML insights endpoint for demo cloning
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@@ -1858,6 +1858,124 @@ class ProductionService:
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)
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raise
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async def get_ai_waste_impact(
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self,
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tenant_id: UUID,
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start_date: datetime,
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end_date: datetime
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) -> Dict[str, Any]:
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"""
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Get AI impact on waste reduction
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Compares waste rates between AI-assisted and manual batches
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to demonstrate ROI of AI features for sustainability.
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"""
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try:
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async with self.database_manager.get_session() as session:
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from app.repositories.production_batch_repository import ProductionBatchRepository
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from sqlalchemy import text
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batch_repo = ProductionBatchRepository(session)
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# Query for AI vs manual batch comparison
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query = text("""
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SELECT
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-- AI-assisted batches
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COUNT(CASE WHEN is_ai_assisted = true THEN 1 END) as ai_batches,
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COALESCE(SUM(CASE WHEN is_ai_assisted = true THEN planned_quantity ELSE 0 END), 0) as ai_planned,
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COALESCE(SUM(CASE WHEN is_ai_assisted = true THEN actual_quantity ELSE 0 END), 0) as ai_actual,
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COALESCE(SUM(CASE WHEN is_ai_assisted = true THEN waste_quantity ELSE 0 END), 0) as ai_waste,
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COALESCE(SUM(CASE WHEN is_ai_assisted = true THEN defect_quantity ELSE 0 END), 0) as ai_defects,
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-- Manual batches
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COUNT(CASE WHEN is_ai_assisted = false THEN 1 END) as manual_batches,
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COALESCE(SUM(CASE WHEN is_ai_assisted = false THEN planned_quantity ELSE 0 END), 0) as manual_planned,
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COALESCE(SUM(CASE WHEN is_ai_assisted = false THEN actual_quantity ELSE 0 END), 0) as manual_actual,
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COALESCE(SUM(CASE WHEN is_ai_assisted = false THEN waste_quantity ELSE 0 END), 0) as manual_waste,
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COALESCE(SUM(CASE WHEN is_ai_assisted = false THEN defect_quantity ELSE 0 END), 0) as manual_defects
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FROM production_batches
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WHERE tenant_id = :tenant_id
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AND created_at BETWEEN :start_date AND :end_date
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AND status IN ('COMPLETED', 'QUALITY_CHECK')
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""")
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result = await session.execute(
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query,
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{
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'tenant_id': tenant_id,
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'start_date': start_date,
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'end_date': end_date
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}
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)
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row = result.fetchone()
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# Calculate waste percentages
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ai_total_waste = float(row.ai_waste or 0) + float(row.ai_defects or 0)
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manual_total_waste = float(row.manual_waste or 0) + float(row.manual_defects or 0)
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ai_waste_pct = (ai_total_waste / float(row.ai_planned)) * 100 if row.ai_planned > 0 else 0
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manual_waste_pct = (manual_total_waste / float(row.manual_planned)) * 100 if row.manual_planned > 0 else 0
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# Calculate reduction
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waste_reduction_pct = 0
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if manual_waste_pct > 0:
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waste_reduction_pct = ((manual_waste_pct - ai_waste_pct) / manual_waste_pct) * 100
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# Calculate waste avoided
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if manual_waste_pct > 0 and row.ai_planned > 0:
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waste_avoided_kg = (float(row.ai_planned) * (manual_waste_pct / 100)) - ai_total_waste
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else:
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waste_avoided_kg = 0
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# Financial impact (€3.50/kg average waste cost)
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waste_cost_avoided = waste_avoided_kg * 3.50
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ai_impact_data = {
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'ai_batches': {
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'count': int(row.ai_batches or 0),
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'production_kg': float(row.ai_planned or 0),
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'waste_kg': ai_total_waste,
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'waste_percentage': round(ai_waste_pct, 2)
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},
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'manual_batches': {
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'count': int(row.manual_batches or 0),
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'production_kg': float(row.manual_planned or 0),
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'waste_kg': manual_total_waste,
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'waste_percentage': round(manual_waste_pct, 2)
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},
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'impact': {
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'waste_reduction_percentage': round(waste_reduction_pct, 1),
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'waste_avoided_kg': round(waste_avoided_kg, 2),
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'cost_savings_eur': round(waste_cost_avoided, 2),
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'annual_projection_eur': round(waste_cost_avoided * 12, 2)
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},
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'adoption': {
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'ai_adoption_rate': round((int(row.ai_batches or 0) / (int(row.ai_batches or 0) + int(row.manual_batches or 1))) * 100, 1),
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'recommendation': 'increase_ai_usage' if waste_reduction_pct > 10 else 'monitor'
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},
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'period': {
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'start_date': start_date.isoformat(),
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'end_date': end_date.isoformat()
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}
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}
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logger.info(
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"AI waste impact calculated",
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tenant_id=str(tenant_id),
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waste_reduction_pct=waste_reduction_pct,
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waste_avoided_kg=waste_avoided_kg
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)
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return ai_impact_data
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except Exception as e:
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logger.error(
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"Error calculating AI waste impact",
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tenant_id=str(tenant_id),
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error=str(e)
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)
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raise
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# ================================================================
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# NEW: ORCHESTRATOR INTEGRATION
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# ================================================================
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Reference in New Issue
Block a user