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feat: 路线图R1决策建议一键落地+R2机会推送+R5预算闭环

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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
This commit is contained in:
Hermes CI Fix
2026-08-30 12:05:36 +08:00
parent 5b920df8a0
commit ad68471b29
22 changed files with 2170 additions and 25 deletions
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backend/app/api/ai_analysis.py
+201 -10
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@@ -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