335 lines
13 KiB
Python
335 lines
13 KiB
Python
"""预警 API"""
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from fastapi import APIRouter, Depends, Query, HTTPException
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from sqlalchemy.orm import Session
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from app.database import get_db
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from app.auth_middleware import require_auth, require_role
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from app.models import KPIAlert, OperationLog, ActionPlan
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import logging
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logger = logging.getLogger("cma.alerts")
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router = APIRouter(prefix="/api/cma/alerts", tags=["预警"],
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dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
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)
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@router.get("")
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def list_alerts(status: str = None, page: int = Query(1, ge=1), db: Session = Depends(get_db)):
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query = db.query(KPIAlert)
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if status:
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query = query.filter(KPIAlert.status == status)
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total = query.count()
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alerts = query.order_by(KPIAlert.created_at.desc()).offset((page-1)*20).limit(20).all()
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return {"total": total, "data": [{c.name: getattr(a, c.name) for c in KPIAlert.__table__.columns} for a in alerts]}
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@router.post("/{alert_id}/resolve")
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def resolve_alert(alert_id: int, data: dict, db: Session = Depends(get_db)):
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alert = db.query(KPIAlert).filter(KPIAlert.id == alert_id).first()
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if not alert:
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raise HTTPException(404, "预警不存在")
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alert.status = "resolved"
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alert.resolution = data.get("resolution", "")
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alert.assignee = data.get("assignee", alert.assignee)
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from datetime import datetime; alert.resolved_at = datetime.now()
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db.commit()
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db.refresh(alert)
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return {
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"message": "已处理",
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"assignee": alert.assignee,
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"alert": {c.name: getattr(alert, c.name) for c in KPIAlert.__table__.columns},
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"suggest_create_action_plan": alert.alert_level == "red",
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}
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@router.post("/{alert_id}/process")
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def process_alert(alert_id: int, data: dict, db: Session = Depends(get_db)):
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"""标记预警为处理中"""
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alert = db.query(KPIAlert).filter(KPIAlert.id == alert_id).first()
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if not alert:
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raise HTTPException(404, "预警不存在")
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if alert.status == "resolved":
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raise HTTPException(400, "已处理的预警不能重复处理")
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assignee = data.get("assignee")
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if not assignee:
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raise HTTPException(400, "缺少处理人")
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alert.status = "processing"
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alert.assignee = assignee
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db.commit()
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db.refresh(alert)
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return {"message": "已标记为处理中", "alert": {c.name: getattr(alert, c.name) for c in KPIAlert.__table__.columns}}
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@router.post("/{alert_id}/escalate")
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def escalate_alert(alert_id: int, data: dict, db: Session = Depends(get_db)):
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"""升级预警级别"""
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alert = db.query(KPIAlert).filter(KPIAlert.id == alert_id).first()
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if not alert:
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raise HTTPException(404, "预警不存在")
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assignee = data.get("assignee")
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if not assignee:
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raise HTTPException(400, "缺少处理人")
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if alert.status == "resolved":
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raise HTTPException(400, "已处理的预警不能升级")
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if alert.alert_level != "red":
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alert.alert_level = "red"
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alert.assignee = assignee
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db.commit()
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db.refresh(alert)
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return {"message": "已升级", "alert": {c.name: getattr(alert, c.name) for c in KPIAlert.__table__.columns}}
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@router.get("/check-timeout")
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def check_alert_timeout(db: Session = Depends(get_db)):
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"""超时预警检测 — 超过24小时未处理的pending预警自动升级为红色"""
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from datetime import datetime, timedelta
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cutoff = datetime.now() - timedelta(hours=24)
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timeout_alerts = db.query(KPIAlert).filter(
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KPIAlert.status == "pending",
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KPIAlert.created_at < cutoff,
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KPIAlert.alert_level != "red",
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).all()
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upgraded_count = 0
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for alert in timeout_alerts:
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alert.alert_level = "red"
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alert.status = "processing"
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upgraded_count += 1
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if upgraded_count:
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db.commit()
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return {"total_timeout": len(timeout_alerts), "upgraded_count": upgraded_count}
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@router.post("/{alert_id}/create-action-plan")
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def create_action_plan_from_alert(alert_id: int, data: dict, db: Session = Depends(get_db)):
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"""从预警创建改善行动计划"""
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alert = db.query(KPIAlert).filter(KPIAlert.id == alert_id).first()
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if not alert:
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raise HTTPException(404, "预警不存在")
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if alert.action_plan_linked_id:
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raise HTTPException(400, "已关联改善计划")
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plan = ActionPlan(
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alert_id=alert.id,
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kpi_id=alert.kpi_id,
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title=f"改善: {alert.alert_message}",
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assignee=data.get("assignee", ""),
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priority="high" if alert.alert_level == "red" else "medium",
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created_by=data.get("created_by", ""),
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)
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db.add(plan)
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db.commit()
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db.refresh(plan)
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alert.action_plan_linked_id = plan.id
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db.commit()
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return {"message": "改善行动计划已创建", "plan_id": plan.id, "priority": plan.priority}
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# ──────────────────────────────────────────────
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# 功能4: 风险矩阵热力图 (CMA P2 - ERM框架、风险识别四象限)
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RISK_MATRIX_DATA = {
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"hanke": {
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"entity_name": "陕西酣客（白酒经销）",
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"quadrants": [
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{
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"impact": "high",
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"probability": "high",
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"label": "高影响×高概率",
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"risks": [
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{
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"id": "risk_001",
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"name": "流动性风险",
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"impact_label": "高",
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"probability_label": "高",
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"detail": "现金2.2万 vs 短债350万 → 断流风险",
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"impact_value": 90,
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"probability_value": 85,
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"type": "red",
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"measures": ["催收大额应收", "协商短期借款续贷"],
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"responsible": "任富海",
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"deadline": "7月底",
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},
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{
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"id": "risk_002",
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"name": "合规风险",
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"impact_label": "高",
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"probability_label": "高",
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"detail": "欠税426万 · 折旧违规",
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"impact_value": 95,
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"probability_value": 80,
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"type": "red",
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"measures": ["补缴欠税计划", "重新梳理折旧政策"],
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"responsible": "任富海",
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"deadline": "8月底",
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},
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],
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},
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{
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"impact": "high",
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"probability": "medium",
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"label": "高影响×中概率",
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"risks": [
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{
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"id": "risk_003",
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"name": "政策风险",
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"impact_label": "高",
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"probability_label": "中",
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"detail": "白酒消费税调整可能导致成本上升15-20%",
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"impact_value": 85,
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"probability_value": 50,
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"type": "orange",
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"measures": ["关注政策动向", "预留税务缓冲资金"],
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"responsible": "财务部",
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"deadline": "持续关注",
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},
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],
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},
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{
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"impact": "medium",
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"probability": "high",
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"label": "中影响×高概率",
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"risks": [
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{
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"id": "risk_004",
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"name": "运营风险",
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"impact_label": "中",
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"probability_label": "高",
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"detail": "Model C 成本模型未落地，成本核算偏差",
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"impact_value": 60,
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"probability_value": 80,
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"type": "yellow",
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"measures": ["推动Model C落地", "建立成本标准化流程"],
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"responsible": "财务部",
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"deadline": "8月中",
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},
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],
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},
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{
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"impact": "medium",
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"probability": "medium",
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"label": "中影响×中概率",
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"risks": [
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{
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"id": "risk_005",
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"name": "战略风险",
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"impact_label": "中",
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"probability_label": "中",
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"detail": "酒类零交易，新业务方向不确定",
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"impact_value": 55,
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"probability_value": 55,
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"type": "yellow",
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"measures": ["制定新业务评估框架", "定期战略复盘"],
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"responsible": "管理层",
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"deadline": "9月底",
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},
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],
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},
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{
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"impact": "low",
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"probability": "low",
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"label": "低影响×低概率",
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"risks": [
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{
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"id": "risk_006",
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"name": "市场风险",
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"impact_label": "低",
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"probability_label": "低",
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"detail": "行业需求波动，但酣客已基本退出市场",
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"impact_value": 25,
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"probability_value": 20,
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"type": "green",
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"measures": ["定期监控行业数据"],
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"responsible": "业务部",
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"deadline": "每季度",
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},
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{
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"id": "risk_007",
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"name": "人员风险",
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"impact_label": "低",
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"probability_label": "低",
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"detail": "核心团队稳定，短期内无流失风险",
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"impact_value": 20,
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"probability_value": 15,
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"type": "green",
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"measures": ["保持团队激励", "关键岗位备份"],
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"responsible": "人事部",
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"deadline": "持续",
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},
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],
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},
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],
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},
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"bohai": {
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"entity_name": "陕西博海科技（IT服务）",
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"quadrants": [
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{
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"impact": "high",
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"probability": "medium",
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"label": "高影响×中概率",
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"risks": [
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{
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"id": "risk_b_001",
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"name": "现金流风险",
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"impact_label": "高",
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"probability_label": "中",
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"detail": "应收账款账期延长，现金流紧张",
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"impact_value": 85,
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"probability_value": 55,
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"type": "orange",
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"measures": ["加快应收催收", "建立信用管理制度"],
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"responsible": "任富海",
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"deadline": "7月底",
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},
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],
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},
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{
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"impact": "medium",
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"probability": "high",
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"label": "中影响×高概率",
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"risks": [
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{
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"id": "risk_b_002",
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"name": "项目交付风险",
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"impact_label": "中",
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"probability_label": "高",
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"detail": "多个项目并行，交付压力大",
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"impact_value": 65,
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"probability_value": 75,
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"type": "yellow",
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"measures": ["优化项目排期", "增加外包资源"],
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"responsible": "项目部",
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"deadline": "持续",
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},
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],
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},
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{
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"impact": "low",
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"probability": "medium",
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"label": "低影响×中概率",
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"risks": [
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{
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"id": "risk_b_003",
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"name": "技术迭代风险",
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"impact_label": "低",
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"probability_label": "中",
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"detail": "新技术跟踪不及时，可能落后",
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"impact_value": 30,
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"probability_value": 45,
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"type": "green",
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"measures": ["定期技术培训", "技术栈评估"],
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"responsible": "技术部",
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"deadline": "每季度",
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},
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],
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},
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],
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},
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}
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@router.get("/risk-matrix")
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def get_risk_matrix(entity: str = Query("hanke", description="hanke/bohai")):
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"""风险矩阵热力图数据 - CMA P2 ERM四象限"""
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data = RISK_MATRIX_DATA.get(entity)
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if not data:
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data = RISK_MATRIX_DATA["hanke"]
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data["entity_name"] = f"未知实体({entity})，默认返回酣客数据"
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return data
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