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/tests/test_ai_suggestions.py

@@ -0,0 +1,242 @@
+"""
+路线图R1：AI建议→一键落地 测试
+建议CRUD + 应用到KPI/预算/行动方案 + OperationLog留痕 + 已应用/未应用状态
+"""
+import pytest
+from fastapi.testclient import TestClient
+from sqlalchemy.orm import Session
+from datetime import datetime
+
+from tests.conftest import create_test_user, get_token_for_user, auth_header, create_test_kpi
+from app.models import AISuggestion, KPIDefinition, BudgetPlan, ActionPlan, OperationLog, KPIValue
+
+
+def _create_suggestion(client, token, kpi_id, **kw):
+    body = {
+        "suggestion_type": "kpi_target",
+        "target_type": "kpi",
+        "target_id": kpi_id,
+        "title": "上调测试KPI目标",
+        "content": "达成率超预期",
+        "suggestion_data": {"kpi_id": kpi_id, "target_value": 150.0},
+    }
+    body.update(kw)
+    return client.post("/api/cma/ai/suggestions", json=body, headers=auth_header(token))
+
+
+class TestSuggestionCRUD:
+    def test_create_and_list(self, client, db):
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db)
+
+        r = _create_suggestion(client, token, kpi.id)
+        assert r.status_code == 200, r.text
+        data = r.json()["data"]
+        assert data["status"] == "unapplied"
+        assert data["suggestion_type"] == "kpi_target"
+
+        # 列表含未应用
+        lst = client.get("/api/cma/ai/suggestions", headers=auth_header(token)).json()
+        assert lst["total"] == 1
+        assert lst["data"][0]["id"] == data["id"]
+
+        # 详情
+        det = client.get(f"/api/cma/ai/suggestions/{data['id']}", headers=auth_header(token)).json()
+        assert det["data"]["title"] == "上调测试KPI目标"
+
+    def test_create_missing_fields(self, client, db):
+        create_test_user(db)
+        token = get_token_for_user(client)
+        r = client.post("/api/cma/ai/suggestions", json={"title": "无类型"}, headers=auth_header(token))
+        assert r.status_code == 400
+        r2 = client.post("/api/cma/ai/suggestions", json={"suggestion_type": "kpi_target"}, headers=auth_header(token))
+        assert r2.status_code == 400
+
+    def test_apply_kpi_target(self, client, db):
+        """应用建议→改KPI目标→操作日志可查"""
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db, target_value=100.0)
+
+        r = _create_suggestion(client, token, kpi.id)
+        sug_id = r.json()["data"]["id"]
+
+        # 应用：改KPI目标为150
+        app = client.post(
+            f"/api/cma/ai/suggestions/{sug_id}/apply",
+            json={"action": "kpi_target", "target_value": 150.0},
+            headers=auth_header(token),
+        )
+        assert app.status_code == 200, app.text
+        app_data = app.json()["data"]
+        assert app_data["status"] == "applied"
+        assert app_data["applied_by"] == "测试管理员"
+        assert app_data["apply_detail"][0]["before"] == 100.0
+        assert app_data["apply_detail"][0]["after"] == 150.0
+
+        # KPI目标已变更
+        db.refresh(kpi)
+        assert kpi.target_value == 150.0
+
+        # OperationLog留痕
+        logs = db.query(OperationLog).filter(OperationLog.action == "ai_suggestion_apply").all()
+        assert len(logs) == 1
+        assert logs[0].target_type == "kpi"
+        assert logs[0].target_id == kpi.id
+        assert logs[0].detail["suggestion_id"] == sug_id
+        assert logs[0].detail["before"] == 100.0
+        assert logs[0].detail["after"] == 150.0
+
+        # 重复应用被拒绝
+        app2 = client.post(
+            f"/api/cma/ai/suggestions/{sug_id}/apply",
+            json={"action": "kpi_target", "target_value": 200.0},
+            headers=auth_header(token),
+        )
+        assert app2.status_code == 400
+
+    def test_apply_budget_adjust(self, client, db):
+        """应用建议→调预算（新建/更新BudgetPlan）→操作日志"""
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db)
+
+        r = _create_suggestion(client, token, kpi.id, suggestion_type="budget_adjust",
+                               title="调整预算", suggestion_data={"kpi_id": kpi.id})
+        sug_id = r.json()["data"]["id"]
+
+        app = client.post(
+            f"/api/cma/ai/suggestions/{sug_id}/apply",
+            json={"action": "budget_adjust", "period": "2026-09", "budget_value": 8888.0},
+            headers=auth_header(token),
+        )
+        assert app.status_code == 200, app.text
+        plan = db.query(BudgetPlan).filter(BudgetPlan.kpi_id == kpi.id, BudgetPlan.period == "2026-09").first()
+        assert plan is not None
+        assert plan.budget_value == 8888.0
+        assert plan.source_type == "ai_suggestion"
+
+        # 同期间再应用→更新而非新增
+        app2 = client.post(
+            f"/api/cma/ai/suggestions/{sug_id}/apply",
+            json={"action": "budget_adjust", "period": "2026-09", "budget_value": 9999.0},
+            headers=auth_header(token),
+        )
+        # 已applied被拒；用新建议验证upsert
+        r2 = _create_suggestion(client, token, kpi.id, suggestion_type="budget_adjust",
+                                title="调整预算2", suggestion_data={"kpi_id": kpi.id})
+        sug_id2 = r2.json()["data"]["id"]
+        app3 = client.post(
+            f"/api/cma/ai/suggestions/{sug_id2}/apply",
+            json={"action": "budget_adjust", "period": "2026-09", "budget_value": 9999.0},
+            headers=auth_header(token),
+        )
+        assert app3.status_code == 200
+        plans = db.query(BudgetPlan).filter(BudgetPlan.kpi_id == kpi.id, BudgetPlan.period == "2026-09").all()
+        assert len(plans) == 1
+        assert plans[0].budget_value == 9999.0
+        assert app3.json()["data"]["apply_detail"][0]["before"] == 8888.0
+
+    def test_apply_action_plan(self, client, db):
+        """应用建议→建行动方案→操作日志"""
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db)
+
+        r = _create_suggestion(client, token, kpi.id, suggestion_type="action_plan",
+                               title="建行动方案", suggestion_data={"kpi_id": kpi.id})
+        sug_id = r.json()["data"]["id"]
+
+        app = client.post(
+            f"/api/cma/ai/suggestions/{sug_id}/apply",
+            json={"action": "action_plan", "title": "营收提升专项", "assignee": "张三",
+                  "priority": "high", "due_date": "2026-09-30"},
+            headers=auth_header(token),
+        )
+        assert app.status_code == 200, app.text
+        plan = db.query(ActionPlan).filter(ActionPlan.kpi_id == kpi.id, ActionPlan.title == "营收提升专项").first()
+        assert plan is not None
+        assert plan.assignee == "张三"
+        assert plan.priority == "high"
+        assert plan.created_by == "测试管理员"
+
+        logs = db.query(OperationLog).filter(OperationLog.action == "ai_suggestion_apply",
+                                             OperationLog.target_type == "action_plan").all()
+        assert len(logs) == 1
+        assert logs[0].target_id == plan.id
+
+    def test_dismiss(self, client, db):
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db)
+        r = _create_suggestion(client, token, kpi.id)
+        sug_id = r.json()["data"]["id"]
+
+        d = client.post(f"/api/cma/ai/suggestions/{sug_id}/dismiss", headers=auth_header(token))
+        assert d.status_code == 200
+        det = client.get(f"/api/cma/ai/suggestions/{sug_id}", headers=auth_header(token)).json()
+        assert det["data"]["status"] == "dismissed"
+        # 忽略后应用被拒
+        app = client.post(f"/api/cma/ai/suggestions/{sug_id}/apply",
+                          json={"action": "kpi_target", "target_value": 1}, headers=auth_header(token))
+        assert app.status_code == 400
+
+    def test_apply_not_found(self, client, db):
+        create_test_user(db)
+        token = get_token_for_user(client)
+        app = client.post("/api/cma/ai/suggestions/9999/apply", json={}, headers=auth_header(token))
+        assert app.status_code == 404
+
+
+class TestRuleSuggestions:
+    """dashboard-analysis 自动生成建议（规则驱动）"""
+
+    def test_generate_low_ratio_action(self, client, db):
+        """执行率<70% → 生成建行动方案建议"""
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db, target_value=100.0)
+        db.add(KPIValue(kpi_id=kpi.id, period="2026-06", actual_value=50.0))
+        db.commit()
+
+        # 直接调规则生成
+        resp = client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token))
+        assert resp.status_code == 200
+        s = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).all()
+        assert len(s) >= 1
+        assert any(x.suggestion_type == "action_plan" for x in s)
+
+        # 幂等：再调一次不重复建
+        resp2 = client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token))
+        s2 = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).all()
+        assert len(s2) == len(s)
+
+    def test_generate_high_ratio_target(self, client, db):
+        """执行率>110% → 生成上调目标建议"""
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db, target_value=100.0)
+        db.add(KPIValue(kpi_id=kpi.id, period="2026-06", actual_value=150.0))
+        db.commit()
+
+        resp = client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token))
+        assert resp.status_code == 200
+        s = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).all()
+        assert any(x.suggestion_type == "kpi_target" for x in s)
+        assert "suggestions" in resp.json()
+
+    def test_generate_budget_overrun(self, client, db):
+        """预算执行率>110% → 生成调预算建议"""
+        create_test_user(db)
+        token = get_token_for_user(client)
+        kpi = create_test_kpi(db, target_value=100.0)
+        db.add(KPIValue(kpi_id=kpi.id, period="2026-08", actual_value=200.0))
+        db.add(BudgetPlan(entity_id=1, kpi_id=kpi.id, period="2026-08", budget_value=100.0,
+                          budget_year=2026, budget_month=8, status="active"))
+        db.commit()
+
+        resp = client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token))
+        assert resp.status_code == 200
+        s = db.query(AISuggestion).filter(AISuggestion.suggestion_type == "budget_adjust").all()
+        assert len(s) >= 1