Improve the UI and tests
This commit is contained in:
Urtzi Alfaro
@@ -11,10 +11,12 @@ 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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import asyncio
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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 ..utils.cache import get_cached, set_cached, delete_pattern
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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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@@ -194,45 +196,59 @@ async def get_bakery_health_status(
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or if there are issues requiring attention.
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"""
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try:
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# Try to get from cache
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if settings.CACHE_ENABLED:
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cache_key = f"dashboard:health:{tenant_id}"
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cached = await get_cached(cache_key)
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if cached:
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return BakeryHealthStatusResponse(**cached)
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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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# Gather metrics from various services in parallel
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# Use asyncio.gather to make all HTTP calls concurrently
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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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async def fetch_alerts():
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try:
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alerts_data = await alerts_client.get_alerts_summary(tenant_id) or {}
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return 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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return 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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async def fetch_pending_pos():
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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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return 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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return 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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async def fetch_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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return 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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return 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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async def fetch_inventory():
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try:
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inv_data = await inventory_client.get_inventory_dashboard(tenant_id) or {}
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return 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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return 0
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# Execute all fetches in parallel
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critical_alerts, pending_approvals, production_delays, out_of_stock_count = await asyncio.gather(
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fetch_alerts(),
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fetch_pending_pos(),
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fetch_production_delays(),
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fetch_inventory()
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)
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# System errors (would come from monitoring system)
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system_errors = 0
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@@ -247,6 +263,11 @@ async def get_bakery_health_status(
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system_errors=system_errors
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)
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# Cache the result
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if settings.CACHE_ENABLED:
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cache_key = f"dashboard:health:{tenant_id}"
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await set_cached(cache_key, health_status, ttl=settings.CACHE_TTL_HEALTH)
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return BakeryHealthStatusResponse(**health_status)
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except Exception as e:
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@@ -267,6 +288,13 @@ async def get_orchestration_summary(
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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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# Try to get from cache (only if no specific run_id is provided)
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if settings.CACHE_ENABLED and run_id is None:
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cache_key = f"dashboard:summary:{tenant_id}"
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cached = await get_cached(cache_key)
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if cached:
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return OrchestrationSummaryResponse(**cached)
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dashboard_service = DashboardService(db)
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# Get orchestration summary
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@@ -307,6 +335,11 @@ async def get_orchestration_summary(
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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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# Cache the result (only if no specific run_id)
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if settings.CACHE_ENABLED and run_id is None:
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cache_key = f"dashboard:summary:{tenant_id}"
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await set_cached(cache_key, summary, ttl=settings.CACHE_TTL_SUMMARY)
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return OrchestrationSummaryResponse(**summary)
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except Exception as e:
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@@ -328,38 +361,52 @@ async def get_action_queue(
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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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# Fetch data from various services in parallel
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async def fetch_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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return po_data
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return []
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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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return []
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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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async def fetch_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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return alerts_data.get("alerts", [])
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return []
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except Exception as e:
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logger.warning(f"Failed to fetch alerts: {e}")
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return []
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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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async def fetch_onboarding():
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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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return {
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"incomplete": not onboarding_data.get("completed", True),
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"steps": onboarding_data.get("steps", [])
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}
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return {"incomplete": False, "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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return {"incomplete": False, "steps": []}
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# Execute all fetches in parallel
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pending_pos, critical_alerts, onboarding = await asyncio.gather(
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fetch_pending_pos(),
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fetch_critical_alerts(),
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fetch_onboarding()
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)
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onboarding_incomplete = onboarding["incomplete"]
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onboarding_steps = onboarding["steps"]
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# Build action queue
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actions = await dashboard_service.get_action_queue(
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@@ -443,93 +490,106 @@ async def get_insights(
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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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# Try to get from cache
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if settings.CACHE_ENABLED:
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cache_key = f"dashboard:insights:{tenant_id}"
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cached = await get_cached(cache_key)
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if cached:
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return InsightsResponse(**cached)
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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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# Fetch data from various services in parallel
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from datetime import datetime, timedelta, timezone
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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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async def fetch_sustainability():
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try:
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return 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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return {}
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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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async def fetch_inventory():
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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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return 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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return {
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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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return {}
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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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return {}
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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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async def fetch_deliveries():
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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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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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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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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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# 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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return {"deliveries_today": deliveries_today}
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return {}
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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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return {}
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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):
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weekly_savings = 0
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# Calculate savings from price optimization
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for po in pos_result:
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# Check if PO was created in last 7 days
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created_at = po.get("created_at")
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if created_at:
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if isinstance(created_at, str):
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created_at = datetime.fromisoformat(created_at.replace('Z', '+00:00'))
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if created_at >= seven_days_ago:
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# Sum up savings from optimization
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optimization_data = po.get("optimization_data", {})
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if isinstance(optimization_data, dict):
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savings = optimization_data.get("savings", 0) or 0
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weekly_savings += float(savings)
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async def fetch_savings():
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try:
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# Get recent POs (last 7 days) and sum up optimization savings
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seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
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# Default trend percentage (would need historical data for real trend)
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savings_data = {
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"weekly_savings": round(weekly_savings, 2),
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"trend_percentage": 12 if weekly_savings > 0 else 0
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}
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else:
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savings_data = {"weekly_savings": 0, "trend_percentage": 0}
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except Exception as e:
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logger.warning(f"Failed to calculate savings data: {e}")
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savings_data = {"weekly_savings": 0, "trend_percentage": 0}
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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):
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weekly_savings = 0
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# Calculate savings from price optimization
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for po in pos_result:
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# Check if PO was created in last 7 days
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created_at = po.get("created_at")
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if created_at:
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if isinstance(created_at, str):
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created_at = datetime.fromisoformat(created_at.replace('Z', '+00:00'))
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if created_at >= seven_days_ago:
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# Sum up savings from optimization
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optimization_data = po.get("optimization_data", {})
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if isinstance(optimization_data, dict):
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savings = optimization_data.get("savings", 0) or 0
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weekly_savings += float(savings)
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# Default trend percentage (would need historical data for real trend)
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return {
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"weekly_savings": round(weekly_savings, 2),
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"trend_percentage": 12 if weekly_savings > 0 else 0
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}
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return {"weekly_savings": 0, "trend_percentage": 0}
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except Exception as e:
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logger.warning(f"Failed to calculate savings data: {e}")
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return {"weekly_savings": 0, "trend_percentage": 0}
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# Execute all fetches in parallel
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sustainability_data, inventory_data, delivery_data, savings_data = await asyncio.gather(
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fetch_sustainability(),
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fetch_inventory(),
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fetch_deliveries(),
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fetch_savings()
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)
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# Merge delivery data into inventory data
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inventory_data.update(delivery_data)
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@@ -542,6 +602,19 @@ async def get_insights(
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savings_data=savings_data
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)
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# Prepare response
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response_data = {
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"savings": insights["savings"],
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"inventory": insights["inventory"],
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"waste": insights["waste"],
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"deliveries": insights["deliveries"]
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}
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# Cache the result
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if settings.CACHE_ENABLED:
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cache_key = f"dashboard:insights:{tenant_id}"
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await set_cached(cache_key, response_data, ttl=settings.CACHE_TTL_INSIGHTS)
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|
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return InsightsResponse(
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savings=InsightCard(**insights["savings"]),
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inventory=InsightCard(**insights["inventory"]),
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@@ -103,6 +103,15 @@ class OrchestratorSettings(BaseServiceSettings):
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AI_INSIGHTS_SERVICE_URL: str = os.getenv("AI_INSIGHTS_SERVICE_URL", "http://ai-insights-service:8000")
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AI_INSIGHTS_MIN_CONFIDENCE: int = int(os.getenv("AI_INSIGHTS_MIN_CONFIDENCE", "70"))
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|
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# Redis Cache Settings (for dashboard performance)
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REDIS_HOST: str = os.getenv("REDIS_HOST", "localhost")
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REDIS_PORT: int = int(os.getenv("REDIS_PORT", "6379"))
|
||||
REDIS_DB: int = int(os.getenv("REDIS_DB", "0"))
|
||||
CACHE_ENABLED: bool = os.getenv("CACHE_ENABLED", "true").lower() == "true"
|
||||
CACHE_TTL_HEALTH: int = int(os.getenv("CACHE_TTL_HEALTH", "30")) # 30 seconds
|
||||
CACHE_TTL_INSIGHTS: int = int(os.getenv("CACHE_TTL_INSIGHTS", "120")) # 2 minutes
|
||||
CACHE_TTL_SUMMARY: int = int(os.getenv("CACHE_TTL_SUMMARY", "60")) # 1 minute
|
||||
|
||||
|
||||
# Global settings instance
|
||||
settings = OrchestratorSettings()
|
||||
|
||||
219
services/orchestrator/app/utils/cache.py
Normal file
219
services/orchestrator/app/utils/cache.py
Normal file
@@ -0,0 +1,219 @@
|
||||
# services/orchestrator/app/utils/cache.py
|
||||
"""
|
||||
Redis caching utilities for dashboard endpoints
|
||||
"""
|
||||
|
||||
import json
|
||||
import redis.asyncio as redis
|
||||
from typing import Optional, Any, Callable
|
||||
from functools import wraps
|
||||
import structlog
|
||||
from app.core.config import settings
|
||||
|
||||
logger = structlog.get_logger()
|
||||
|
||||
# Redis client instance
|
||||
_redis_client: Optional[redis.Redis] = None
|
||||
|
||||
|
||||
async def get_redis_client() -> redis.Redis:
|
||||
"""Get or create Redis client"""
|
||||
global _redis_client
|
||||
|
||||
if _redis_client is None:
|
||||
try:
|
||||
_redis_client = redis.Redis(
|
||||
host=getattr(settings, 'REDIS_HOST', 'localhost'),
|
||||
port=getattr(settings, 'REDIS_PORT', 6379),
|
||||
db=getattr(settings, 'REDIS_DB', 0),
|
||||
decode_responses=True,
|
||||
socket_connect_timeout=5,
|
||||
socket_timeout=5
|
||||
)
|
||||
# Test connection
|
||||
await _redis_client.ping()
|
||||
logger.info("Redis client connected successfully")
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to connect to Redis: {e}. Caching will be disabled.")
|
||||
_redis_client = None
|
||||
|
||||
return _redis_client
|
||||
|
||||
|
||||
async def close_redis():
|
||||
"""Close Redis connection"""
|
||||
global _redis_client
|
||||
if _redis_client:
|
||||
await _redis_client.close()
|
||||
_redis_client = None
|
||||
logger.info("Redis connection closed")
|
||||
|
||||
|
||||
async def get_cached(key: str) -> Optional[Any]:
|
||||
"""
|
||||
Get cached value by key
|
||||
|
||||
Args:
|
||||
key: Cache key
|
||||
|
||||
Returns:
|
||||
Cached value (deserialized from JSON) or None if not found or error
|
||||
"""
|
||||
try:
|
||||
client = await get_redis_client()
|
||||
if not client:
|
||||
return None
|
||||
|
||||
cached = await client.get(key)
|
||||
if cached:
|
||||
logger.debug(f"Cache hit: {key}")
|
||||
return json.loads(cached)
|
||||
else:
|
||||
logger.debug(f"Cache miss: {key}")
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.warning(f"Cache get error for key {key}: {e}")
|
||||
return None
|
||||
|
||||
|
||||
async def set_cached(key: str, value: Any, ttl: int = 60) -> bool:
|
||||
"""
|
||||
Set cached value with TTL
|
||||
|
||||
Args:
|
||||
key: Cache key
|
||||
value: Value to cache (will be JSON serialized)
|
||||
ttl: Time to live in seconds
|
||||
|
||||
Returns:
|
||||
True if successful, False otherwise
|
||||
"""
|
||||
try:
|
||||
client = await get_redis_client()
|
||||
if not client:
|
||||
return False
|
||||
|
||||
serialized = json.dumps(value, default=str)
|
||||
await client.setex(key, ttl, serialized)
|
||||
logger.debug(f"Cache set: {key} (TTL: {ttl}s)")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning(f"Cache set error for key {key}: {e}")
|
||||
return False
|
||||
|
||||
|
||||
async def delete_cached(key: str) -> bool:
|
||||
"""
|
||||
Delete cached value
|
||||
|
||||
Args:
|
||||
key: Cache key
|
||||
|
||||
Returns:
|
||||
True if successful, False otherwise
|
||||
"""
|
||||
try:
|
||||
client = await get_redis_client()
|
||||
if not client:
|
||||
return False
|
||||
|
||||
await client.delete(key)
|
||||
logger.debug(f"Cache deleted: {key}")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning(f"Cache delete error for key {key}: {e}")
|
||||
return False
|
||||
|
||||
|
||||
async def delete_pattern(pattern: str) -> int:
|
||||
"""
|
||||
Delete all keys matching pattern
|
||||
|
||||
Args:
|
||||
pattern: Redis key pattern (e.g., "dashboard:*")
|
||||
|
||||
Returns:
|
||||
Number of keys deleted
|
||||
"""
|
||||
try:
|
||||
client = await get_redis_client()
|
||||
if not client:
|
||||
return 0
|
||||
|
||||
keys = []
|
||||
async for key in client.scan_iter(match=pattern):
|
||||
keys.append(key)
|
||||
|
||||
if keys:
|
||||
deleted = await client.delete(*keys)
|
||||
logger.info(f"Deleted {deleted} keys matching pattern: {pattern}")
|
||||
return deleted
|
||||
return 0
|
||||
except Exception as e:
|
||||
logger.warning(f"Cache delete pattern error for {pattern}: {e}")
|
||||
return 0
|
||||
|
||||
|
||||
def cache_response(key_prefix: str, ttl: int = 60):
|
||||
"""
|
||||
Decorator to cache endpoint responses
|
||||
|
||||
Args:
|
||||
key_prefix: Prefix for cache key (will be combined with tenant_id)
|
||||
ttl: Time to live in seconds
|
||||
|
||||
Usage:
|
||||
@cache_response("dashboard:health", ttl=30)
|
||||
async def get_health(tenant_id: str):
|
||||
...
|
||||
"""
|
||||
def decorator(func: Callable):
|
||||
@wraps(func)
|
||||
async def wrapper(*args, **kwargs):
|
||||
# Extract tenant_id from kwargs or args
|
||||
tenant_id = kwargs.get('tenant_id')
|
||||
if not tenant_id and args:
|
||||
# Try to find tenant_id in args (assuming it's the first argument)
|
||||
tenant_id = args[0] if len(args) > 0 else None
|
||||
|
||||
if not tenant_id:
|
||||
# No tenant_id, skip caching
|
||||
return await func(*args, **kwargs)
|
||||
|
||||
# Build cache key
|
||||
cache_key = f"{key_prefix}:{tenant_id}"
|
||||
|
||||
# Try to get from cache
|
||||
cached_value = await get_cached(cache_key)
|
||||
if cached_value is not None:
|
||||
return cached_value
|
||||
|
||||
# Execute function
|
||||
result = await func(*args, **kwargs)
|
||||
|
||||
# Cache result
|
||||
await set_cached(cache_key, result, ttl)
|
||||
|
||||
return result
|
||||
|
||||
return wrapper
|
||||
return decorator
|
||||
|
||||
|
||||
def make_cache_key(prefix: str, tenant_id: str, **params) -> str:
|
||||
"""
|
||||
Create a cache key with optional parameters
|
||||
|
||||
Args:
|
||||
prefix: Key prefix
|
||||
tenant_id: Tenant ID
|
||||
**params: Additional parameters to include in key
|
||||
|
||||
Returns:
|
||||
Cache key string
|
||||
"""
|
||||
key_parts = [prefix, tenant_id]
|
||||
for k, v in sorted(params.items()):
|
||||
if v is not None:
|
||||
key_parts.append(f"{k}:{v}")
|
||||
return ":".join(key_parts)
|
||||
Reference in New Issue
Block a user