feat: 路线图R1决策建议一键落地+R2机会推送+R5预算闭环

R1(P0): AI建议一键应用到KPI/预算/行动方案
- 新表 ai_suggestions + AISuggestion 模型(init_db自动建)
- /api/cma/ai/suggestions CRUD + /{id}/apply(复用kpis/budget/action_plans) + dismiss
- 应用写 OperationLog(action=ai_suggestion_apply, detail含suggestion_id/before/after)
- 规则驱动建议生成 generate_rule_suggestions(低执行率/高执行率/预算超支/pending预警)
- 幂等: 同entity+type+target_id+title+unapplied不重复建; applied后拒绝重复应用
- 前端: Dashboard AI面板建议卡(应用到/忽略) + 建议中心页 /ai-suggestions

R2(P1): 数据找人扩大-机会类推送
- scripts/opportunity_detector.py: KPI向好(执行率>110%)/预算余量(<70%且actual>0)/预测上行
- scripts/daily_push.py: 异常+机会 每日9:15推企微(8800/send, --dry-run调试)
- crontab: 15 9 * * * (alert_generator 9:00之后)

R5(P0): 预算闭环加固
- auto-decompose批量幂等: 只取年度行(period=YYYY-00)+同KPI多版本取一行
- scripts/closed_loop_check.py: 预算执行率异常→检查现金流/行动同步→缺失提示+报告
- scripts/verify_decompose_idempotent.py: 幂等验证脚本

测试: test_ai_suggestions(10例)+test_roadmap_r2r5(14例); 修test_budget幂等契约适配年度行
全量: 673 passed

backend/app/api/ai_analysis.py

@@ -2,17 +2,185 @@
 from fastapi import APIRouter, Depends, HTTPException, Query, Request
 from fastapi.responses import StreamingResponse
 from sqlalchemy.orm import Session
-from sqlalchemy import func, text as sa_text
+from sqlalchemy import func, text as sa_text, or_
 from app.database import get_db
+from app.deps import get_entity_id
 from app.auth_middleware import require_auth, require_role
-from app.models import KPIDefinition, KPIValue, KPIAlert, StrategicMap, User, ActionPlan
+from app.models import KPIDefinition, KPIValue, KPIAlert, StrategicMap, User, ActionPlan, BudgetPlan, AISuggestion
 from app.utils.cache import get as cache_get, set as cache_set
 import json, hashlib, httpx, os
-from datetime import datetime
+from datetime import datetime, date
 router = APIRouter(prefix="/api/cma/ai", tags=["AI分析"],
     dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
 )
 
+
+# ============================================================
+# R1 决策建议生成（规则驱动，稳定可复现，落库 ai_suggestions）
+# ============================================================
+def _sug_dict(s: AISuggestion) -> dict:
+    return {
+        "id": s.id,
+        "entity_id": s.entity_id,
+        "source": s.source,
+        "suggestion_type": s.suggestion_type,
+        "target_type": s.target_type,
+        "target_id": s.target_id,
+        "title": s.title,
+        "content": s.content,
+        "suggestion_data": s.suggestion_data or {},
+        "status": s.status,
+        "applied_by": s.applied_by,
+        "applied_at": s.applied_at.isoformat() if s.applied_at else None,
+        "apply_detail": s.apply_detail or [],
+        "created_at": s.created_at.isoformat() if s.created_at else None,
+    }
+
+
+def _existing_unapplied(db: Session, entity_id: int, suggestion_type: str,
+                        target_id: int, title: str) -> bool:
+    """幂等：同entity+类型+目标+标题的未应用建议存在则跳过"""
+    return db.query(AISuggestion).filter(
+        AISuggestion.entity_id == entity_id,
+        AISuggestion.suggestion_type == suggestion_type,
+        AISuggestion.target_id == target_id,
+        AISuggestion.title == title,
+        AISuggestion.status == "unapplied",
+    ).first() is not None
+
+
+def generate_rule_suggestions(db: Session, entity_id: int,
+                              source: str = "dashboard", user_id: int = None,
+                              kpi_id: int = None) -> list:
+    """从数据规则生成决策建议并落库（R1，路线图2026-08-30）
+
+    规则：
+      1. KPI执行率<70% → 建议建行动方案（异常类）
+      2. KPI执行率>110% → 建议上调KPI目标（机会类）
+      3. 预算执行率>110% → 建议调预算（预算类）
+      4. 有pending预警 → 建议建行动方案处理预警
+    幂等：同 entity+type+target_id+title+status=unapplied 不重复建。
+    """
+    now = datetime.now()
+    period = now.strftime("%Y-%m")
+    created = []
+
+    def _add(suggestion_type: str, target_type: str, tid: int,
+             title: str, content: str, suggestion_data: dict):
+        nonlocal created
+        if _existing_unapplied(db, entity_id, suggestion_type, tid, title):
+            return
+        sug = AISuggestion(
+            entity_id=entity_id,
+            user_id=user_id,
+            source=source,
+            suggestion_type=suggestion_type,
+            target_type=target_type,
+            target_id=tid,
+            title=title,
+            content=content,
+            suggestion_data=suggestion_data,
+            status="unapplied",
+        )
+        db.add(sug)
+        created.append(sug)
+
+    # 查询KPI（可按kpi_id过滤）
+    q = db.query(KPIDefinition).filter(KPIDefinition.entity_id == entity_id,
+                                       KPIDefinition.status == "active")
+    if kpi_id:
+        q = q.filter(KPIDefinition.id == kpi_id)
+    kpis = q.all()
+
+    for k in kpis:
+        latest = db.query(KPIValue).filter(
+            KPIValue.kpi_id == k.id,
+            or_(
+                KPIValue.entity_id == entity_id,
+                KPIValue.entity_id.is_(None),
+            ),
+        ).order_by(KPIValue.period.desc()).first()
+        if not latest or latest.actual_value is None:
+            continue
+        actual = latest.actual_value
+        target = k.target_value
+        ratio = (actual / target) if target else None
+
+        # 1. 异常：执行率<70% → 建行动方案
+        if ratio is not None and ratio < 0.7:
+            title = f"提升 {k.kpi_name}：达成率仅{ratio*100:.0f}%"
+            content = (f"KPI[{k.kpi_name}] 最新期间{latest.period}实际值{actual:g}，"
+                       f"目标{target:g}，达成率{ratio*100:.1f}%，低于70%预警线。"
+                       f"建议制定专项改善行动方案。")
+            _add("action_plan", "kpi", k.id, title, content, {
+                "kpi_id": k.id, "priority": "high",
+                "title": f"改善: {k.kpi_name}达成率提升",
+            })
+        # 2. 机会：执行率>110% → 上调KPI目标
+        elif ratio is not None and ratio > 1.1:
+            new_target = round(actual * 1.05, 2)
+            title = f"上调 {k.kpi_name} 目标：达成率{ratio*100:.0f}%超预期"
+            content = (f"KPI[{k.kpi_name}] 达成率{ratio*100:.1f}%超过110%，"
+                       f"建议将目标从{target:g}上调至{new_target:g}，保持牵引力。")
+            _add("kpi_target", "kpi", k.id, title, content, {
+                "kpi_id": k.id, "target_value": new_target,
+            })
+
+    # 3. 预算执行率>110% → 调预算
+    budget_rows = db.query(BudgetPlan).filter(
+        BudgetPlan.entity_id == entity_id,
+        BudgetPlan.status == "active",
+        BudgetPlan.period == period,
+    ).all()
+    for b in budget_rows:
+        actual = db.query(func.max(KPIValue.actual_value)).filter(
+            KPIValue.kpi_id == b.kpi_id,
+            KPIValue.period == b.period,
+        ).scalar()
+        if actual is None or b.budget_value is None or b.budget_value <= 0:
+            continue
+        exec_ratio = actual / b.budget_value
+        if exec_ratio > 1.1:
+            kpi_name = "KPI"
+            k = db.query(KPIDefinition).filter(KPIDefinition.id == b.kpi_id).first()
+            if k:
+                kpi_name = k.kpi_name
+            title = f"调整 {kpi_name} 预算：执行率{exec_ratio*100:.0f}%超预算"
+            content = (f"预算[{kpi_name}] {period}预算值{b.budget_value:g}，"
+                       f"实际{actual:g}，执行率{exec_ratio*100:.1f}%超过110%。"
+                       f"建议同步调整预算/现金流/行动方案。")
+            _add("budget_adjust", "budget", b.kpi_id, title, content, {
+                "kpi_id": b.kpi_id, "period": period, "budget_value": round(actual, 2),
+            })
+
+    # 4. pending预警 → 建行动方案
+    alerts = db.query(KPIAlert).filter(KPIAlert.status == "pending").all()
+    for a in alerts:
+        k = db.query(KPIDefinition).filter(KPIDefinition.id == a.kpi_id).first()
+        kpi_name = k.kpi_name if k else f"KPI#{a.kpi_id}"
+        title = f"处理预警：{kpi_name} {a.alert_message[:30]}"
+        content = f"存在待处理预警（{a.alert_level}级）：{a.alert_message}。建议建立行动方案跟进。"
+        _add("action_plan", "alert", a.id, title, content, {
+            "kpi_id": a.kpi_id, "priority": "high" if a.alert_level == "red" else "medium",
+            "alert_id": a.id,
+            "title": f"处理预警: {kpi_name}",
+        })
+
+    if created:
+        db.commit()
+        for s in created:
+            db.refresh(s)
+    return created
+
+
+def _unapplied_suggestions(db: Session, entity_id: int, limit: int = 20) -> list:
+    items = db.query(AISuggestion).filter(
+        AISuggestion.entity_id == entity_id,
+        AISuggestion.status == "unapplied",
+    ).order_by(AISuggestion.created_at.desc()).limit(limit).all()
+    return [_sug_dict(s) for s in items]
+
+
 async def _call_deepseek(prompt: str) -> str:
     """调用DeepSeek API"""
     api_key = os.getenv("DEEPSEEK_API_KEY", "sk-8e24e6eb87f2475e96ea0980002dc2e8")
@@ -34,15 +202,23 @@ async def _call_deepseek(prompt: str) -> str:
         return data.get("choices", [{}])[0].get("message", {}).get("content", "")
 
 @router.get("/dashboard-analysis")
-async def dashboard_analysis(role: str = Query("ceo"), db: Session = Depends(get_db)):
+async def dashboard_analysis(role: str = Query("ceo"), db: Session = Depends(get_db),
+                             entity_id: int = Depends(get_entity_id)):
     """AI分析驾驶舱数据"""
     # 尝试缓存
-    cache_key = f"dashboard_analysis:{role}"
+    cache_key = f"dashboard_analysis:{role}:{entity_id}"
     cached = cache_get("ai", cache_key)
     if cached:
+        # 缓存命中（LLM文本10分钟内不重复调用），但轻量规则建议仍执行（幂等）
+        try:
+            generate_rule_suggestions(db, entity_id, source="dashboard")
+        except Exception:
+            pass
+        cached["suggestions"] = _unapplied_suggestions(db, entity_id)
         return cached
     # 获取当前KPI数据
-    kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
+    kpis = db.query(KPIDefinition).filter(KPIDefinition.entity_id == entity_id,
+                                          KPIDefinition.status == "active").all()
     kpi_summary = []
     for k in kpis:
         latest = db.query(KPIValue).filter(KPIValue.kpi_id == k.id).order_by(KPIValue.period.desc()).first()
@@ -81,17 +257,25 @@ async def dashboard_analysis(role: str = Query("ceo"), db: Session = Depends(get
     except Exception as e:
         analysis = f"AI分析暂时不可用: {str(e)}"
     
-    result = {"analysis": analysis, "kpi_count": len(kpi_summary), "alert_count": alerts}
+    # R1: 规则驱动生成可落地决策建议（幂等落库）
+    try:
+        generate_rule_suggestions(db, entity_id, source="dashboard")
+    except Exception as e:
+        pass
+    
+    result = {"analysis": analysis, "kpi_count": len(kpi_summary), "alert_count": alerts,
+              "suggestions": _unapplied_suggestions(db, entity_id)}
     # 缓存10分钟
     cache_set("ai", cache_key, result, ttl_seconds=600)
     return result
 
 
 @router.get("/kpi-analysis/{kpi_id}")
-async def kpi_analysis(kpi_id: int, db: Session = Depends(get_db)):
+async def kpi_analysis(kpi_id: int, db: Session = Depends(get_db),
+                       entity_id: int = Depends(get_entity_id)):
     """AI分析单个KPI"""
     # 尝试缓存
-    cache_key = f"kpi_analysis:{kpi_id}"
+    cache_key = f"kpi_analysis:{kpi_id}:{entity_id}"
     cached = cache_get("ai", cache_key)
     if cached:
         return cached
@@ -129,7 +313,14 @@ KPI名称：{kpi.kpi_name}
     except Exception as e:
         analysis = f"分析暂时不可用: {str(e)}"
     
-    result = {"kpi_name": kpi.kpi_name, "analysis": analysis}
+    # R1: 生成该KPI的可落地建议
+    try:
+        generate_rule_suggestions(db, entity_id, source="kpi", kpi_id=kpi_id)
+    except Exception as e:
+        pass
+    
+    result = {"kpi_name": kpi.kpi_name, "analysis": analysis,
+              "suggestions": _unapplied_suggestions(db, entity_id)}
     cache_set("ai", cache_key, result, ttl_seconds=600)
     return result
 

backend/app/api/ai_suggestions.py

@@ -0,0 +1,336 @@
+"""AI决策建议 — 一键应用到KPI/预算/行动方案 (路线图R1 2026-08-30)
+
+北极星④决策闭环：AI建议 → 点击应用 → 写库变更 → OperationLog留痕 → 前端可查已应用/未应用。
+应用动作复用现有 kpis/budget/action_plans 数据模型，不新建业务接口。
+"""
+from fastapi import APIRouter, Depends, HTTPException, Query, Request
+from sqlalchemy.orm import Session
+from sqlalchemy import func
+from typing import Optional
+from datetime import datetime
+
+from app.database import get_db
+from app.deps import get_entity_id, resolve_entity_for_request
+from app.auth_middleware import require_auth, require_role
+from app.models import AISuggestion, KPIDefinition, KPIValue, OperationLog, BudgetPlan, ActionPlan
+
+router = APIRouter(prefix="/api/cma/ai/suggestions", tags=["AI建议"],
+    dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
+)
+
+
+def _sug_dict(s: AISuggestion) -> dict:
+    return {
+        "id": s.id,
+        "entity_id": s.entity_id,
+        "user_id": s.user_id,
+        "source": s.source,
+        "suggestion_type": s.suggestion_type,
+        "target_type": s.target_type,
+        "target_id": s.target_id,
+        "title": s.title,
+        "content": s.content,
+        "suggestion_data": s.suggestion_data or {},
+        "status": s.status,
+        "applied_by": s.applied_by,
+        "applied_at": s.applied_at.isoformat() if s.applied_at else None,
+        "apply_detail": s.apply_detail or [],
+        "created_at": s.created_at.isoformat() if s.created_at else None,
+    }
+
+
+@router.post("")
+def create_suggestion(
+    request: Request,
+    data: dict,
+    db: Session = Depends(get_db),
+    current_user=Depends(require_auth),
+):
+    """创建AI建议（前端AI分析/手动保存建议）"""
+    suggestion_type = data.get("suggestion_type") or data.get("type")
+    title = (data.get("title") or "").strip()
+    if not suggestion_type:
+        raise HTTPException(400, "缺少 suggestion_type (kpi_target/budget_adjust/action_plan)")
+    if not title:
+        raise HTTPException(400, "缺少 title")
+
+    entity_id = resolve_entity_for_request(request, data.get("entity_id") or 1)
+
+    sug = AISuggestion(
+        entity_id=entity_id,
+        user_id=getattr(current_user, "id", None),
+        source=data.get("source", "manual"),
+        suggestion_type=suggestion_type,
+        target_type=data.get("target_type", "kpi"),
+        target_id=data.get("target_id"),
+        title=title,
+        content=data.get("content"),
+        suggestion_data=data.get("suggestion_data") or {},
+        status="unapplied",
+    )
+    db.add(sug)
+    db.commit()
+    db.refresh(sug)
+    return {"success": True, "message": "建议已保存", "data": _sug_dict(sug)}
+
+
+@router.get("")
+def list_suggestions(
+    status: Optional[str] = Query(None, description="unapplied/applied/dismissed"),
+    suggestion_type: Optional[str] = Query(None),
+    entity_id: int = Depends(get_entity_id),
+    db: Session = Depends(get_db),
+):
+    """建议列表（前端建议中心/详情页查看已应用/未应用状态）"""
+    query = db.query(AISuggestion).filter(AISuggestion.entity_id == entity_id)
+    if status:
+        query = query.filter(AISuggestion.status == status)
+    if suggestion_type:
+        query = query.filter(AISuggestion.suggestion_type == suggestion_type)
+    items = query.order_by(AISuggestion.created_at.desc()).limit(200).all()
+    return {"data": [_sug_dict(s) for s in items], "total": len(items)}
+
+
+@router.get("/{suggestion_id}")
+def get_suggestion(suggestion_id: int, db: Session = Depends(get_db)):
+    """建议详情"""
+    s = db.query(AISuggestion).filter(AISuggestion.id == suggestion_id).first()
+    if not s:
+        raise HTTPException(404, "建议不存在")
+    return {"data": _sug_dict(s)}
+
+
+def _apply_kpi_target(db: Session, sug: AISuggestion, params: dict, current_user) -> dict:
+    """改KPI目标"""
+    target_value = params.get("target_value")
+    if target_value is None:
+        raise HTTPException(400, "应用kpi_target需要 target_value")
+    kpi_id = params.get("kpi_id") or sug.target_id
+    if not kpi_id:
+        raise HTTPException(400, "缺少 kpi_id")
+    kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
+    if not kpi:
+        raise HTTPException(404, f"KPI {kpi_id} 不存在")
+    before = kpi.target_value
+    kpi.target_value = float(target_value)
+    db.flush()
+    detail_item = {
+        "target_type": "kpi",
+        "target_id": kpi.id,
+        "target_name": kpi.kpi_name,
+        "action": "update_target_value",
+        "before": before,
+        "after": float(target_value),
+    }
+    db.add(OperationLog(
+        user_id=getattr(current_user, "id", None),
+        action="ai_suggestion_apply",
+        target_type="kpi",
+        target_id=kpi.id,
+        detail={
+            "suggestion_id": sug.id,
+            "suggestion_title": sug.title,
+            "apply_action": "kpi_target",
+            "before": before,
+            "after": float(target_value),
+        },
+    ))
+    return detail_item
+
+
+def _apply_budget_adjust(db: Session, sug: AISuggestion, params: dict, current_user) -> dict:
+    """调预算（BudgetPlan upsert，按 kpi_id+period）"""
+    period = params.get("period")
+    budget_value = params.get("budget_value")
+    if not period or budget_value is None:
+        raise HTTPException(400, "应用budget_adjust需要 period + budget_value")
+    kpi_id = params.get("kpi_id") or sug.target_id
+    if not kpi_id:
+        raise HTTPException(400, "缺少 kpi_id")
+    kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
+    if not kpi:
+        raise HTTPException(404, f"KPI {kpi_id} 不存在")
+
+    # 解析期间 2026-09 → year=2026 month=9
+    try:
+        parts = period.split("-")
+        year = int(parts[0])
+        month = int(parts[1])
+    except Exception:
+        raise HTTPException(400, f"period格式错误: {period} (需要 YYYY-MM)")
+
+    plan = db.query(BudgetPlan).filter(
+        BudgetPlan.entity_id == sug.entity_id,
+        BudgetPlan.kpi_id == kpi_id,
+        BudgetPlan.period == period,
+        BudgetPlan.budget_year == year,
+        BudgetPlan.budget_month == month,
+        BudgetPlan.status == "active",
+    ).first()
+
+    before = None
+    if plan:
+        before = plan.budget_value
+        plan.budget_value = float(budget_value)
+    else:
+        plan = BudgetPlan(
+            entity_id=sug.entity_id,
+            kpi_id=kpi_id,
+            period=period,
+            budget_value=float(budget_value),
+            budget_year=year,
+            budget_month=month,
+            version="v1.0",
+            status="active",
+            source_type="ai_suggestion",
+            calc_logic=f"AI建议应用 #{sug.id}: {sug.title}",
+            created_by=getattr(current_user, "name", "") or "",
+        )
+        db.add(plan)
+    db.flush()
+    detail_item = {
+        "target_type": "budget",
+        "target_id": plan.id,
+        "target_name": f"{kpi.kpi_name}[{period}]",
+        "action": "update_budget" if before is not None else "create_budget",
+        "before": before,
+        "after": float(budget_value),
+    }
+    db.add(OperationLog(
+        user_id=getattr(current_user, "id", None),
+        action="ai_suggestion_apply",
+        target_type="budget",
+        target_id=plan.id,
+        detail={
+            "suggestion_id": sug.id,
+            "suggestion_title": sug.title,
+            "apply_action": "budget_adjust",
+            "kpi_id": kpi_id,
+            "period": period,
+            "before": before,
+            "after": float(budget_value),
+        },
+    ))
+    return detail_item
+
+
+def _apply_action_plan(db: Session, sug: AISuggestion, params: dict, current_user) -> dict:
+    """建行动方案"""
+    title = (params.get("title") or "").strip() or sug.title
+    kpi_id = params.get("kpi_id") or sug.target_id
+    if not kpi_id:
+        raise HTTPException(400, "缺少 kpi_id")
+    kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
+    if not kpi:
+        raise HTTPException(404, f"KPI {kpi_id} 不存在")
+
+    due_date = None
+    if params.get("due_date"):
+        try:
+            due_date = datetime.strptime(str(params["due_date"])[:10], "%Y-%m-%d")
+        except Exception:
+            due_date = None
+
+    plan = ActionPlan(
+        kpi_id=kpi_id,
+        title=title,
+        description=params.get("description") or sug.content or f"由AI建议 #{sug.id} 生成: {sug.title}",
+        assignee=params.get("assignee") or "",
+        priority=params.get("priority") or "medium",
+        due_date=due_date,
+        status="pending",
+        progress=0,
+        created_by=getattr(current_user, "name", "") or "ai_suggestion",
+    )
+    db.add(plan)
+    db.flush()
+    detail_item = {
+        "target_type": "action_plan",
+        "target_id": plan.id,
+        "target_name": title,
+        "action": "create_action_plan",
+        "before": None,
+        "after": plan.id,
+    }
+    db.add(OperationLog(
+        user_id=getattr(current_user, "id", None),
+        action="ai_suggestion_apply",
+        target_type="action_plan",
+        target_id=plan.id,
+        detail={
+            "suggestion_id": sug.id,
+            "suggestion_title": sug.title,
+            "apply_action": "action_plan",
+            "kpi_id": kpi_id,
+            "plan_title": title,
+        },
+    ))
+    return detail_item
+
+
+_APPLYERS = {
+    "kpi_target": _apply_kpi_target,
+    "budget_adjust": _apply_budget_adjust,
+    "action_plan": _apply_action_plan,
+}
+
+
+@router.post("/{suggestion_id}/apply")
+def apply_suggestion(
+    suggestion_id: int,
+    data: dict,
+    db: Session = Depends(get_db),
+    current_user=Depends(require_auth),
+):
+    """应用建议：改KPI目标 / 调预算 / 建行动方案（写库+操作日志留痕）
+
+    Body 示例:
+      {"action": "kpi_target", "target_value": 2000000}
+      {"action": "budget_adjust", "period": "2026-09", "budget_value": 100000}
+      {"action": "action_plan", "title": "...", "assignee": "...", "priority": "high", "due_date": "2026-09-30"}
+    """
+    sug = db.query(AISuggestion).filter(AISuggestion.id == suggestion_id).first()
+    if not sug:
+        raise HTTPException(404, "建议不存在")
+    if sug.status == "applied":
+        raise HTTPException(400, "该建议已应用，不能重复应用")
+    if sug.status == "dismissed":
+        raise HTTPException(400, "该建议已忽略，如需应用请重新创建")
+
+    action = data.get("action") or sug.suggestion_type
+    applier = _APPLYERS.get(action)
+    if not applier:
+        raise HTTPException(400, f"不支持的应用动作: {action} (支持 kpi_target/budget_adjust/action_plan)")
+
+    # 应用参数 = 请求体参数 覆盖 建议默认参数
+    params = dict(sug.suggestion_data or {})
+    params.update({k: v for k, v in data.items() if k != "action" and v is not None})
+
+    detail_item = applier(db, sug, params, current_user)
+    sug.status = "applied"
+    sug.applied_by = getattr(current_user, "name", "") or ""
+    sug.applied_user_id = getattr(current_user, "id", None)
+    sug.applied_at = datetime.now()
+    sug.apply_detail = [detail_item]
+    db.commit()
+    db.refresh(sug)
+    return {
+        "success": True,
+        "message": "建议已应用并留痕",
+        "data": _sug_dict(sug),
+    }
+
+
+@router.post("/{suggestion_id}/dismiss")
+def dismiss_suggestion(
+    suggestion_id: int,
+    db: Session = Depends(get_db),
+    current_user=Depends(require_auth),
+):
+    """忽略建议"""
+    sug = db.query(AISuggestion).filter(AISuggestion.id == suggestion_id).first()
+    if not sug:
+        raise HTTPException(404, "建议不存在")
+    sug.status = "dismissed"
+    db.commit()
+    return {"success": True, "message": "建议已忽略"}

backend/app/main.py

@@ -5,7 +5,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
 from dotenv import load_dotenv
 from app.database import init_db
-from app.api import auth, kpis, kpi_governance, templates, maps, dashboard, data, alerts, ai_analysis, alert_rules, users, thresholds, notifications, permissions, action_plans, alignment, org, objectives, versions, budget, cost, predict, reports, security, knowledge, bot_bridge, bot_bridge_v2, lead, tenant, customer_dashboard, deviation_push, budget_generate, knowledge_articles, kpi_causality, data_quality, bi_reports, entities, bsc_layers, okr, okr_templates, subjects, driver_budget, bot_kpis, ontology, bot_iron_law, analysis_results, expenses, cash, tax_compliance, verify, growth_quality, products, data_classification, value_sources, zero_based, derivation_rules, cash_classify
+from app.api import auth, kpis, kpi_governance, templates, maps, dashboard, data, alerts, ai_analysis, ai_suggestions, alert_rules, users, thresholds, notifications, permissions, action_plans, alignment, org, objectives, versions, budget, cost, predict, reports, security, knowledge, bot_bridge, bot_bridge_v2, lead, tenant, customer_dashboard, deviation_push, budget_generate, knowledge_articles, kpi_causality, data_quality, bi_reports, entities, bsc_layers, okr, okr_templates, subjects, driver_budget, bot_kpis, ontology, bot_iron_law, analysis_results, expenses, cash, tax_compliance, verify, growth_quality, products, data_classification, value_sources, zero_based, derivation_rules, cash_classify
 from app.utils.cache import clear_all as clear_cache, delete as delete_cache
 from scripts.erp_sync import run_sync as run_erp_sync
 from app.auth_middleware import require_auth
@@ -43,6 +43,7 @@ app.include_router(dashboard.router)
 app.include_router(data.router)
 app.include_router(alerts.router)
 app.include_router(ai_analysis.router)
+app.include_router(ai_suggestions.router)
 app.include_router(alert_rules.router)
 app.include_router(users.router)
 app.include_router(thresholds.router)

backend/app/models/__init__.py

@@ -911,3 +911,25 @@ class CashPlanUnclassified(Base):
     status = Column(String(20), default="pending", comment="pending/classified/ignored")
     created_at = Column(DateTime, server_default=func.now())
     resolved_at = Column(DateTime, nullable=True)
+
+
+class AISuggestion(Base):
+    """AI决策建议 — 一键应用到KPI/预算/行动方案 (路线图R1 2026-08-30)"""
+    __tablename__ = "ai_suggestions"
+    id = Column(Integer, primary_key=True, index=True)
+    entity_id = Column(Integer, default=1, comment="企业ID")
+    user_id = Column(Integer, nullable=True, comment="建议创建人ID")
+    source = Column(String(30), default="dashboard", comment="来源: dashboard/kpi/budget/manual/rule")
+    suggestion_type = Column(String(30), nullable=False, comment="kpi_target/budget_adjust/action_plan")
+    target_type = Column(String(30), nullable=False, comment="kpi/budget/action_plan")
+    target_id = Column(Integer, nullable=True, comment="目标ID (KPI ID/预算KPI ID等)")
+    title = Column(String(300), nullable=False, comment="建议标题")
+    content = Column(Text, nullable=True, comment="建议内容/理由")
+    suggestion_data = Column(JSON, nullable=True, comment="应用参数: {target_value, period, budget_value, plan_title, ...}")
+    status = Column(String(20), default="unapplied", comment="unapplied/applied/dismissed")
+    applied_by = Column(String(100), nullable=True, comment="应用人姓名")
+    applied_user_id = Column(Integer, nullable=True, comment="应用人ID")
+    applied_at = Column(DateTime, nullable=True, comment="应用时间")
+    apply_detail = Column(JSON, nullable=True, comment="应用结果明细: [{target_type,target_id,action,before,after}]")
+    created_at = Column(DateTime, server_default=func.now())
+    updated_at = Column(DateTime, server_default=func.now(), onupdate=func.now())