555 lines
22 KiB
Python
555 lines
22 KiB
Python
# ================================================================
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# services/orchestrator/app/api/dashboard.py
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# ================================================================
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"""
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Dashboard API endpoints for JTBD-aligned bakery dashboard
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"""
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from fastapi import APIRouter, Depends, HTTPException, Query
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from sqlalchemy.ext.asyncio import AsyncSession
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from typing import Dict, Any, List, Optional
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from pydantic import BaseModel, Field
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from datetime import datetime
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import logging
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from app.core.database import get_db
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from app.core.config import settings
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from ..services.dashboard_service import DashboardService
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from shared.clients import (
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get_inventory_client,
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get_production_client,
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get_alerts_client,
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ProductionServiceClient,
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InventoryServiceClient,
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AlertsServiceClient
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)
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from shared.clients.procurement_client import ProcurementServiceClient
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logger = logging.getLogger(__name__)
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# Initialize service clients
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inventory_client = get_inventory_client(settings, "orchestrator")
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production_client = get_production_client(settings, "orchestrator")
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procurement_client = ProcurementServiceClient(settings)
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alerts_client = get_alerts_client(settings, "orchestrator")
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router = APIRouter(prefix="/api/v1/tenants/{tenant_id}/dashboard", tags=["dashboard"])
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# ============================================================
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# Response Models
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# ============================================================
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class HeadlineData(BaseModel):
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"""i18n-ready headline data"""
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key: str = Field(..., description="i18n translation key")
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params: Dict[str, Any] = Field(default_factory=dict, description="Parameters for translation")
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class HealthChecklistItem(BaseModel):
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"""Individual item in health checklist"""
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icon: str = Field(..., description="Icon name: check, warning, alert")
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text: Optional[str] = Field(None, description="Deprecated: Use textKey instead")
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textKey: Optional[str] = Field(None, description="i18n translation key")
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textParams: Optional[Dict[str, Any]] = Field(None, description="Parameters for i18n translation")
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actionRequired: bool = Field(..., description="Whether action is required")
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class BakeryHealthStatusResponse(BaseModel):
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"""Overall bakery health status"""
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status: str = Field(..., description="Health status: green, yellow, red")
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headline: HeadlineData = Field(..., description="i18n-ready status headline")
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lastOrchestrationRun: Optional[str] = Field(None, description="ISO timestamp of last orchestration")
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nextScheduledRun: str = Field(..., description="ISO timestamp of next scheduled run")
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checklistItems: List[HealthChecklistItem] = Field(..., description="Status checklist")
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criticalIssues: int = Field(..., description="Count of critical issues")
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pendingActions: int = Field(..., description="Count of pending actions")
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class ReasoningInputs(BaseModel):
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"""Inputs used by orchestrator for decision making"""
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customerOrders: int = Field(..., description="Number of customer orders analyzed")
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historicalDemand: bool = Field(..., description="Whether historical data was used")
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inventoryLevels: bool = Field(..., description="Whether inventory levels were considered")
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aiInsights: bool = Field(..., description="Whether AI insights were used")
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class PurchaseOrderSummary(BaseModel):
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"""Summary of a purchase order for dashboard"""
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supplierName: str
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itemCategories: List[str]
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totalAmount: float
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class ProductionBatchSummary(BaseModel):
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"""Summary of a production batch for dashboard"""
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productName: str
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quantity: float
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readyByTime: str
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class OrchestrationSummaryResponse(BaseModel):
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"""What the orchestrator did for the user"""
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runTimestamp: Optional[str] = Field(None, description="When the orchestration ran")
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runNumber: Optional[str] = Field(None, description="Run number identifier")
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status: str = Field(..., description="Run status")
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purchaseOrdersCreated: int = Field(..., description="Number of POs created")
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purchaseOrdersSummary: List[PurchaseOrderSummary] = Field(default_factory=list)
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productionBatchesCreated: int = Field(..., description="Number of batches created")
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productionBatchesSummary: List[ProductionBatchSummary] = Field(default_factory=list)
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reasoningInputs: ReasoningInputs
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userActionsRequired: int = Field(..., description="Number of actions needing approval")
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durationSeconds: Optional[int] = Field(None, description="How long orchestration took")
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aiAssisted: bool = Field(False, description="Whether AI insights were used")
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message: Optional[str] = Field(None, description="User-friendly message")
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class ActionButton(BaseModel):
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"""Action button configuration"""
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label: str
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type: str = Field(..., description="Button type: primary, secondary, tertiary")
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action: str = Field(..., description="Action identifier")
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class ActionItem(BaseModel):
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"""Individual action requiring user attention"""
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id: str
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type: str = Field(..., description="Action type")
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urgency: str = Field(..., description="Urgency: critical, important, normal")
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title: str
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subtitle: str
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reasoning: str = Field(..., description="Why this action is needed")
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consequence: str = Field(..., description="What happens if not done")
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amount: Optional[float] = Field(None, description="Amount for financial actions")
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currency: Optional[str] = Field(None, description="Currency code")
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actions: List[ActionButton]
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estimatedTimeMinutes: int
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class ActionQueueResponse(BaseModel):
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"""Prioritized queue of actions"""
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actions: List[ActionItem]
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totalActions: int
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criticalCount: int
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importantCount: int
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class ProductionTimelineItem(BaseModel):
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"""Individual production batch in timeline"""
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id: str
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batchNumber: str
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productName: str
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quantity: float
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unit: str
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plannedStartTime: Optional[str]
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plannedEndTime: Optional[str]
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actualStartTime: Optional[str]
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status: str
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statusIcon: str
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statusText: str
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progress: int = Field(..., ge=0, le=100, description="Progress percentage")
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readyBy: Optional[str]
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priority: str
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reasoning: str
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class ProductionTimelineResponse(BaseModel):
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"""Today's production timeline"""
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timeline: List[ProductionTimelineItem]
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totalBatches: int
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completedBatches: int
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inProgressBatches: int
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pendingBatches: int
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class InsightCard(BaseModel):
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"""Individual insight card"""
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label: str
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value: str
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detail: str
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color: str = Field(..., description="Color: green, amber, red")
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class InsightsResponse(BaseModel):
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"""Key insights grid"""
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savings: InsightCard
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inventory: InsightCard
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waste: InsightCard
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deliveries: InsightCard
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# ============================================================
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# API Endpoints
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# ============================================================
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@router.get("/health-status", response_model=BakeryHealthStatusResponse)
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async def get_bakery_health_status(
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tenant_id: str,
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db: AsyncSession = Depends(get_db)
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) -> BakeryHealthStatusResponse:
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"""
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Get overall bakery health status
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This is the top-level indicator showing if the bakery is running smoothly
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or if there are issues requiring attention.
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"""
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try:
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dashboard_service = DashboardService(db)
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# Gather metrics from various services
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# In a real implementation, these would be fetched from respective services
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# For now, we'll make HTTP calls to the services
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# Get alerts summary
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try:
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alerts_data = await alerts_client.get_alerts_summary(tenant_id) or {}
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critical_alerts = alerts_data.get("critical_count", 0)
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except Exception as e:
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logger.warning(f"Failed to fetch alerts: {e}")
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critical_alerts = 0
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# Get pending PO count
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try:
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po_data = await procurement_client.get_pending_purchase_orders(tenant_id, limit=100) or []
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pending_approvals = len(po_data) if isinstance(po_data, list) else 0
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except Exception as e:
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logger.warning(f"Failed to fetch POs: {e}")
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pending_approvals = 0
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# Get production delays
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try:
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prod_data = await production_client.get_production_batches_by_status(
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tenant_id, status="ON_HOLD", limit=100
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) or {}
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production_delays = len(prod_data.get("batches", []))
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except Exception as e:
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logger.warning(f"Failed to fetch production batches: {e}")
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production_delays = 0
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# Get inventory status
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try:
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inv_data = await inventory_client.get_inventory_dashboard(tenant_id) or {}
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out_of_stock_count = inv_data.get("out_of_stock_count", 0)
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except Exception as e:
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logger.warning(f"Failed to fetch inventory: {e}")
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out_of_stock_count = 0
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# System errors (would come from monitoring system)
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system_errors = 0
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# Calculate health status
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health_status = await dashboard_service.get_bakery_health_status(
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tenant_id=tenant_id,
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critical_alerts=critical_alerts,
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pending_approvals=pending_approvals,
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production_delays=production_delays,
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out_of_stock_count=out_of_stock_count,
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system_errors=system_errors
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)
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return BakeryHealthStatusResponse(**health_status)
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except Exception as e:
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logger.error(f"Error getting health status: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/orchestration-summary", response_model=OrchestrationSummaryResponse)
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async def get_orchestration_summary(
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tenant_id: str,
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run_id: Optional[str] = Query(None, description="Specific run ID, or latest if not provided"),
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db: AsyncSession = Depends(get_db)
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) -> OrchestrationSummaryResponse:
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"""
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Get narrative summary of what the orchestrator did
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This provides transparency into the automation, showing what was planned
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and why, helping build user trust in the system.
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"""
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try:
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dashboard_service = DashboardService(db)
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# Get orchestration summary
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summary = await dashboard_service.get_orchestration_summary(
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tenant_id=tenant_id,
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last_run_id=run_id
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)
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# Enhance with detailed PO and batch summaries
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if summary["purchaseOrdersCreated"] > 0:
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try:
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po_data = await procurement_client.get_pending_purchase_orders(tenant_id, limit=10)
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if po_data and isinstance(po_data, list):
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summary["purchaseOrdersSummary"] = [
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PurchaseOrderSummary(
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supplierName=po.get("supplier_name", "Unknown"),
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itemCategories=[item.get("ingredient_name", "Item") for item in po.get("items", [])[:3]],
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totalAmount=float(po.get("total_amount", 0))
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)
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for po in po_data[:5] # Show top 5
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]
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except Exception as e:
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logger.warning(f"Failed to fetch PO details: {e}")
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if summary["productionBatchesCreated"] > 0:
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try:
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batch_data = await production_client.get_todays_batches(tenant_id)
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if batch_data:
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batches = batch_data.get("batches", [])
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summary["productionBatchesSummary"] = [
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ProductionBatchSummary(
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productName=batch.get("product_name", "Unknown"),
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quantity=batch.get("planned_quantity", 0),
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readyByTime=batch.get("planned_end_time", "")
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)
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for batch in batches[:5] # Show top 5
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]
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except Exception as e:
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logger.warning(f"Failed to fetch batch details: {e}")
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return OrchestrationSummaryResponse(**summary)
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except Exception as e:
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logger.error(f"Error getting orchestration summary: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/action-queue", response_model=ActionQueueResponse)
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async def get_action_queue(
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tenant_id: str,
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db: AsyncSession = Depends(get_db)
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) -> ActionQueueResponse:
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"""
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Get prioritized queue of actions requiring user attention
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This is the core of the JTBD dashboard - showing exactly what the user
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needs to do right now, prioritized by urgency and impact.
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"""
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try:
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dashboard_service = DashboardService(db)
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# Fetch data from various services
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# Get pending POs
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pending_pos = []
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try:
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po_data = await procurement_client.get_pending_purchase_orders(tenant_id, limit=20)
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if po_data and isinstance(po_data, list):
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pending_pos = po_data
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except Exception as e:
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logger.warning(f"Failed to fetch pending POs: {e}")
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# Get critical alerts
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critical_alerts = []
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try:
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alerts_data = await alerts_client.get_critical_alerts(tenant_id, limit=20)
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if alerts_data:
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critical_alerts = alerts_data.get("alerts", [])
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except Exception as e:
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logger.warning(f"Failed to fetch alerts: {e}")
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# Get onboarding status
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onboarding_incomplete = False
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onboarding_steps = []
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try:
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onboarding_data = await procurement_client.get(
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"/procurement/auth/onboarding-progress",
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tenant_id=tenant_id
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)
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if onboarding_data:
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onboarding_incomplete = not onboarding_data.get("completed", True)
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onboarding_steps = onboarding_data.get("steps", [])
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except Exception as e:
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logger.warning(f"Failed to fetch onboarding status: {e}")
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# Build action queue
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actions = await dashboard_service.get_action_queue(
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tenant_id=tenant_id,
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pending_pos=pending_pos,
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critical_alerts=critical_alerts,
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onboarding_incomplete=onboarding_incomplete,
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onboarding_steps=onboarding_steps
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)
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# Count by urgency
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critical_count = sum(1 for a in actions if a["urgency"] == "critical")
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important_count = sum(1 for a in actions if a["urgency"] == "important")
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return ActionQueueResponse(
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actions=[ActionItem(**action) for action in actions[:10]], # Show top 10
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totalActions=len(actions),
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criticalCount=critical_count,
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importantCount=important_count
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)
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except Exception as e:
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logger.error(f"Error getting action queue: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/production-timeline", response_model=ProductionTimelineResponse)
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async def get_production_timeline(
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tenant_id: str,
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db: AsyncSession = Depends(get_db)
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) -> ProductionTimelineResponse:
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"""
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Get today's production timeline
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Shows what's being made today in chronological order with status and progress.
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"""
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try:
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dashboard_service = DashboardService(db)
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# Fetch today's production batches
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batches = []
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try:
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batch_data = await production_client.get_todays_batches(tenant_id)
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if batch_data:
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batches = batch_data.get("batches", [])
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except Exception as e:
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logger.warning(f"Failed to fetch production batches: {e}")
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# Transform to timeline format
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timeline = await dashboard_service.get_production_timeline(
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tenant_id=tenant_id,
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batches=batches
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)
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# Count by status
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completed = sum(1 for item in timeline if item["status"] == "COMPLETED")
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in_progress = sum(1 for item in timeline if item["status"] == "IN_PROGRESS")
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pending = sum(1 for item in timeline if item["status"] == "PENDING")
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return ProductionTimelineResponse(
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timeline=[ProductionTimelineItem(**item) for item in timeline],
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totalBatches=len(timeline),
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completedBatches=completed,
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inProgressBatches=in_progress,
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pendingBatches=pending
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)
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except Exception as e:
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logger.error(f"Error getting production timeline: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/insights", response_model=InsightsResponse)
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async def get_insights(
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tenant_id: str,
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db: AsyncSession = Depends(get_db)
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) -> InsightsResponse:
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"""
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Get key insights for dashboard grid
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Provides glanceable metrics on savings, inventory, waste, and deliveries.
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"""
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try:
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dashboard_service = DashboardService(db)
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# Fetch data from various services
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# Sustainability data
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sustainability_data = {}
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try:
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sustainability_data = await inventory_client.get_sustainability_widget(tenant_id) or {}
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except Exception as e:
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logger.warning(f"Failed to fetch sustainability data: {e}")
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# Inventory data
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inventory_data = {}
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try:
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raw_inventory_data = await inventory_client.get_stock_status(tenant_id)
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# Handle case where API returns a list instead of dict
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if isinstance(raw_inventory_data, dict):
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inventory_data = raw_inventory_data
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elif isinstance(raw_inventory_data, list):
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# If it's a list, aggregate the data
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inventory_data = {
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"low_stock_count": sum(1 for item in raw_inventory_data if item.get("status") == "low_stock"),
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"out_of_stock_count": sum(1 for item in raw_inventory_data if item.get("status") == "out_of_stock"),
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"total_items": len(raw_inventory_data)
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}
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else:
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inventory_data = {}
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except Exception as e:
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logger.warning(f"Failed to fetch inventory data: {e}")
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# Deliveries data from procurement
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delivery_data = {}
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try:
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# Get recent POs with pending deliveries
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pos_result = await procurement_client.get_pending_purchase_orders(tenant_id, limit=100)
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if pos_result and isinstance(pos_result, list):
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# Count deliveries expected today
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from datetime import datetime, timezone
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today_start = datetime.now(timezone.utc).replace(hour=0, minute=0, second=0, microsecond=0)
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today_end = today_start.replace(hour=23, minute=59, second=59)
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deliveries_today = 0
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for po in pos_result:
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expected_date = po.get("expected_delivery_date")
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if expected_date:
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if isinstance(expected_date, str):
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expected_date = datetime.fromisoformat(expected_date.replace('Z', '+00:00'))
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if today_start <= expected_date <= today_end:
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deliveries_today += 1
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delivery_data = {"deliveries_today": deliveries_today}
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except Exception as e:
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logger.warning(f"Failed to fetch delivery data: {e}")
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# Savings data - Calculate from recent PO price optimizations
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savings_data = {}
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try:
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# Get recent POs (last 7 days) and sum up optimization savings
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from datetime import datetime, timedelta, timezone
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seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
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pos_result = await procurement_client.get_pending_purchase_orders(tenant_id, limit=200)
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if pos_result and isinstance(pos_result, list):
|
|
weekly_savings = 0
|
|
# Calculate savings from price optimization
|
|
for po in pos_result:
|
|
# Check if PO was created in last 7 days
|
|
created_at = po.get("created_at")
|
|
if created_at:
|
|
if isinstance(created_at, str):
|
|
created_at = datetime.fromisoformat(created_at.replace('Z', '+00:00'))
|
|
if created_at >= seven_days_ago:
|
|
# Sum up savings from optimization
|
|
optimization_data = po.get("optimization_data", {})
|
|
if isinstance(optimization_data, dict):
|
|
savings = optimization_data.get("savings", 0) or 0
|
|
weekly_savings += float(savings)
|
|
|
|
# Default trend percentage (would need historical data for real trend)
|
|
savings_data = {
|
|
"weekly_savings": round(weekly_savings, 2),
|
|
"trend_percentage": 12 if weekly_savings > 0 else 0
|
|
}
|
|
else:
|
|
savings_data = {"weekly_savings": 0, "trend_percentage": 0}
|
|
except Exception as e:
|
|
logger.warning(f"Failed to calculate savings data: {e}")
|
|
savings_data = {"weekly_savings": 0, "trend_percentage": 0}
|
|
|
|
# Merge delivery data into inventory data
|
|
inventory_data.update(delivery_data)
|
|
|
|
# Calculate insights
|
|
insights = await dashboard_service.calculate_insights(
|
|
tenant_id=tenant_id,
|
|
sustainability_data=sustainability_data,
|
|
inventory_data=inventory_data,
|
|
savings_data=savings_data
|
|
)
|
|
|
|
return InsightsResponse(
|
|
savings=InsightCard(**insights["savings"]),
|
|
inventory=InsightCard(**insights["inventory"]),
|
|
waste=InsightCard(**insights["waste"]),
|
|
deliveries=InsightCard(**insights["deliveries"])
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error getting insights: {e}", exc_info=True)
|
|
raise HTTPException(status_code=500, detail=str(e))
|