fix: 恢复腾讯云账单同步并完善成本预测

- 接入腾讯云单日账单、全局限频和指数退避

- 修正月末费用预测并增加账期提示和费用归因

- 补充腾讯云限频及账单归因回归测试

frontend/src/components/aiops/AIPredictiveAnalytics.tsx

@@ -54,6 +54,7 @@ export function AIPredictiveAnalytics() {
   const [billingStats, setBillingStats] = useState<JsonData | null>(null);
   const [billingRecords, setBillingRecords] = useState<JsonData[]>([]);
   const [billingAlertRules, setBillingAlertRules] = useState<JsonData[]>([]);
+  const [costAnalysis, setCostAnalysis] = useState<JsonData | null>(null);
 
   useEffect(() => {
     void loadData();
@@ -66,12 +67,13 @@ export function AIPredictiveAnalytics() {
       start.setDate(start.getDate() - 89);
       const startDate = start.toISOString().slice(0, 10);
 
-      const [metricsData, statsResp, billStats, billList, billRules] = await Promise.all([
+      const [metricsData, statsResp, billStats, billList, billRules, analysis] = await Promise.all([
         dashboardStatsApi.getMetrics(72),
         serverApi.getServerStats(),
         billingApi.getStats().catch(() => null),
         billingApi.list({ start_date: startDate, page_size: 500 }).catch(() => ({ list: [] })),
         billingApi.listAlertRules().catch(() => ({ list: [] })),
+        billingApi.getCostAnalysis().catch(() => null),
       ]);
 
       setRawMetrics(Array.isArray(metricsData) ? metricsData : []);
@@ -79,6 +81,7 @@ export function AIPredictiveAnalytics() {
       setBillingStats(billStats);
       setBillingRecords((billList as JsonData)?.list || []);
       setBillingAlertRules((billRules as JsonData)?.list || []);
+      setCostAnalysis(analysis);
     } catch {
       // 保持空数据，组件显示空状态
     } finally {
@@ -104,8 +107,9 @@ export function AIPredictiveAnalytics() {
         billingStats,
         billingRecords,
         billingAlertRules,
+        costAnalysis,
       }),
-    [billingStats, billingRecords, billingAlertRules],
+    [billingStats, billingRecords, billingAlertRules, costAnalysis],
   );
 
   const getTrendIcon = (trend: string) => {
@@ -259,4 +263,4 @@ export function AIPredictiveAnalytics() {
       </Tabs>
     </PageShell>
   );
-}
+}

frontend/src/components/aiops/PredictiveCostTab.tsx

@@ -38,7 +38,7 @@ export function PredictiveCostTab({
   const { t } = useTranslation();
   const [insight, setInsight] = useState('');
   const [analyzing, setAnalyzing] = useState(false);
-  const { summary, dimensionForecasts, budgetRisks, billingPattern, recentDailyAvg } = costData;
+  const { summary, dimensionForecasts, budgetRisks, billingPattern, recentDailyAvg, costAnalysis } = costData;
   const hasData = summary.monthCost > 0 || summary.monthTrend.length > 0;
 
   const getTrendIcon = (trend: string) => {
@@ -129,6 +129,17 @@ export function PredictiveCostTab({
                 </div>
               )}
 
+              {costAnalysis?.incomplete_period && (
+                <div className="flex items-start gap-2 text-sm dg-text-secondary">
+                  <AlertTriangle className="h-4 w-4 dg-text-yellow shrink-0 mt-0.5" />
+                  <span>
+                    {t('aiops.costPredict.incompletePeriod', {
+                      date: costAnalysis.data_through || costAnalysis.analysis_end,
+                    })}
+                  </span>
+                </div>
+              )}
+
               <div className="grid grid-cols-2 md:grid-cols-4 gap-3">
                 <div className="p-3 rounded-lg border border-[var(--dg-border)] bg-[var(--dg-bg-tertiary)]/50">
                   <p className="text-xs dg-text-muted mb-1">{t('aiops.predictivecost.s7g8h9i0j')}</p>
@@ -172,6 +183,58 @@ export function PredictiveCostTab({
         </CardContent>
       </Card>
 
+      {!loading && costAnalysis && costAnalysis.attributions.length > 0 && (
+        <Card className="dg-card">
+          <CardHeader className="pb-3">
+            <CardTitle className="text-[var(--dg-text-primary)] text-base">
+              {t('aiops.costPredict.costAttribution')}
+            </CardTitle>
+          </CardHeader>
+          <CardContent className="space-y-4">
+            <div className="grid grid-cols-1 sm:grid-cols-3 gap-3 text-sm">
+              <div>
+                <p className="text-xs dg-text-muted">{t('aiops.costPredict.baselinePeriod')}</p>
+                <p className="font-semibold text-[var(--dg-text-primary)]">
+                  {formatCurrency(costAnalysis.baseline_cost)}
+                </p>
+                <p className="text-xs dg-text-muted mt-1">{costAnalysis.baseline_period}</p>
+              </div>
+              <div>
+                <p className="text-xs dg-text-muted">{t('aiops.costPredict.comparisonPeriod')}</p>
+                <p className="font-semibold text-[var(--dg-text-primary)]">
+                  {formatCurrency(costAnalysis.comparison_cost)}
+                </p>
+                <p className="text-xs dg-text-muted mt-1">{costAnalysis.comparison_period}</p>
+              </div>
+              <div>
+                <p className="text-xs dg-text-muted">{t('aiops.costPredict.costChange')}</p>
+                <p className={`font-semibold ${costAnalysis.total_delta > 0 ? 'dg-text-red' : 'dg-text-green'}`}>
+                  {costAnalysis.total_delta > 0 ? '+' : ''}{formatCurrency(costAnalysis.total_delta)}
+                </p>
+              </div>
+            </div>
+            <div className="space-y-2">
+              {costAnalysis.attributions.slice(0, 6).map((item) => (
+                <div key={`${item.dimension}-${item.name}`} className="flex items-center justify-between gap-3 text-sm py-1">
+                  <div className="min-w-0">
+                    <span className="dg-text-muted mr-2">
+                      {t(`aiops.costPredict.dimension.${item.dimension}`, { defaultValue: item.dimension })}
+                    </span>
+                    <span className="text-[var(--dg-text-primary)] break-words">{item.name}</span>
+                  </div>
+                  <div className="shrink-0 text-right">
+                    <span className={item.delta > 0 ? 'dg-text-red' : 'dg-text-green'}>
+                      {item.delta > 0 ? '+' : ''}{formatCurrency(item.delta)}
+                    </span>
+                    <span className="dg-text-muted ml-2">{item.contribution.toFixed(1)}%</span>
+                  </div>
+                </div>
+              ))}
+            </div>
+          </CardContent>
+        </Card>
+      )}
+
       {!loading && dimensionForecasts.length > 0 && (
         <Card className="dg-card">
           <CardHeader className="pb-3">
@@ -345,4 +408,4 @@ export function PredictiveCostTab({
       )}
     </div>
   );
-}
+}

frontend/src/components/aiops/cost-predict.ts

@@ -8,6 +8,7 @@ import type {
   CostPredictionSummary,
   ComputedCostPredictions,
   ComputeCostPredictionsInput,
+  CostAnalysis,
 } from './predict-types';
 
 /**
@@ -166,9 +167,18 @@ function forecastMonthEnd(
   const dailyAvg = costs.length > 0 ? costs.reduce((a, b) => a + b, 0) / costs.length : 0;
   const recentDailyAvg = recentRunRate(series);
   const billingPattern = detectBillingPattern(series);
-  // 预付费/前高后平：用近 7 日运行费率外推，避免线性回归高估或矛盾 // Logan.Li
-  const extrapolation =
-    billingPattern === 'front_loaded' ? recentDailyAvg * daysLeft : slope * daysLeft;
+  // 稳态账单逐日累加回归预测值，不能把斜率本身误当成每日费用。 // Logan.Li
+  const intercept = dailyAvg - slope * ((costs.length - 1) / 2);
+  const maxDaily = Math.max(dailyAvg, recentDailyAvg, ...costs, 1) * 3;
+  let extrapolation = 0;
+  if (billingPattern === 'front_loaded') {
+    extrapolation = recentDailyAvg * daysLeft;
+  } else {
+    for (let day = 0; day < daysLeft; day += 1) {
+      const projectedDaily = intercept + slope * (costs.length + day);
+      extrapolation += Math.max(0, Math.min(maxDaily, projectedDaily));
+    }
+  }
   const predictedMonthEnd = Math.max(0, Math.round((currentMonth + extrapolation) * 100) / 100);
   let confidence = Math.round(55 + r2 * 40);
   if (billingPattern === 'front_loaded') confidence = Math.max(45, confidence - 15);
@@ -192,7 +202,7 @@ function forecastMonthEnd(
  * // Logan.Li
  */
 export function computeCostPredictions(input: ComputeCostPredictionsInput): ComputedCostPredictions {
-  const { billingStats, billingRecords, billingAlertRules } = input;
+  const { billingStats, billingRecords, billingAlertRules, costAnalysis } = input;
   const empty: ComputedCostPredictions = {
     summary: {
       monthCost: 0,
@@ -212,6 +222,7 @@ export function computeCostPredictions(input: ComputeCostPredictionsInput): Comp
     recentDailyAvg: 0,
     billingPattern: 'sparse',
     topServices: [],
+    costAnalysis: null,
   };
 
   if (!billingStats) return empty;
@@ -373,6 +384,7 @@ export function computeCostPredictions(input: ComputeCostPredictionsInput): Comp
     recentDailyAvg: overall.recentDailyAvg,
     billingPattern: overall.billingPattern,
     topServices: topServicesByCost(billingRecords),
+    costAnalysis: costAnalysis ? (costAnalysis as unknown as CostAnalysis) : null,
   };
 }
 
@@ -381,7 +393,7 @@ export function computeCostPredictions(input: ComputeCostPredictionsInput): Comp
  * // Logan.Li
  */
 export function buildCostInsightPrompt(data: ComputedCostPredictions): string {
-  const { summary, dimensionForecasts, budgetRisks, recentDailyAvg, billingPattern, topServices } = data;
+  const { summary, dimensionForecasts, budgetRisks, recentDailyAvg, billingPattern, topServices, costAnalysis } = data;
   if (summary.monthCost <= 0 && dimensionForecasts.length === 0) return '';
 
   const patternHint =
@@ -418,6 +430,16 @@ export function buildCostInsightPrompt(data: ComputedCostPredictions): string {
     topServices.length > 0
       ? topServices.map((s) => i18n.t('aiops.costPredict.serviceLine', { service: s.service, cost: s.cost.toFixed(2) }))
       : [`- ${i18n.t('aiops.costPredict.noServiceDetail')}`];
+  const attributionLines = costAnalysis?.attributions?.length
+    ? costAnalysis.attributions.slice(0, 8).map((item) =>
+        i18n.t('aiops.costPredict.attributionLine', {
+          dimension: item.dimension,
+          name: item.name,
+          delta: item.delta.toFixed(2),
+          contribution: item.contribution.toFixed(2),
+        }),
+      )
+    : [`- ${i18n.t('aiops.costPredict.noAttribution')}`];
 
   return [
     i18n.t('aiops.costPredict.promptIntro'),
@@ -427,10 +449,16 @@ export function buildCostInsightPrompt(data: ComputedCostPredictions): string {
     i18n.t('aiops.costPredict.predictedEnd', { amount: summary.predictedMonthEnd.toFixed(2), confidence: summary.confidence }),
     i18n.t('aiops.costPredict.dailySummary', { dailyAvg: summary.dailyAvg.toFixed(2), recentAvg: recentDailyAvg.toFixed(2), daysRemaining: summary.daysRemaining }),
     i18n.t('aiops.costPredict.billingPatternLabel', { hint: patternHint }),
+    costAnalysis?.incomplete_period
+      ? i18n.t('aiops.costPredict.incompletePrompt', { date: costAnalysis.data_through })
+      : '',
     '',
     i18n.t('aiops.costPredict.sectionTopServices'),
     ...serviceLines,
     '',
+    i18n.t('aiops.costPredict.sectionAttribution'),
+    ...attributionLines,
+    '',
     i18n.t('aiops.costPredict.sectionDimensionForecast'),
     ...dimLines,
     '',

frontend/src/components/aiops/predict-types.ts

@@ -77,6 +77,31 @@ export interface CostPredictionSummary {
   providerDist: { provider: string; cost: number; percent: number }[];
 }
 
+/** 后端确定性费用归因结果。 // Logan.Li */
+export interface CostAttribution {
+  dimension: string;
+  name: string;
+  baseline_cost: number;
+  current_cost: number;
+  delta: number;
+  contribution: number;
+}
+
+/** 同期成本分析，供页面展示并作为 AI 事实输入。 // Logan.Li */
+export interface CostAnalysis {
+  analysis_start: string;
+  analysis_end: string;
+  data_through: string;
+  currency: string;
+  incomplete_period: boolean;
+  baseline_period: string;
+  comparison_period: string;
+  baseline_cost: number;
+  comparison_cost: number;
+  total_delta: number;
+  attributions: CostAttribution[];
+}
+
 export interface ComputedCostPredictions {
   summary: CostPredictionSummary;
   dimensionForecasts: CostDimensionForecast[];
@@ -88,6 +113,8 @@ export interface ComputedCostPredictions {
   billingPattern: 'steady' | 'front_loaded' | 'sparse';
   /** 本月 Top 服务消费 */
   topServices: { service: string; cost: number }[];
+  /** 后端按完整数据集计算的同期归因。 // Logan.Li */
+  costAnalysis: CostAnalysis | null;
 }
 
 // ============ 容量预测入参/出参 ============
@@ -114,6 +141,7 @@ export interface ComputeCostPredictionsInput {
   billingStats: JsonData | null;
   billingRecords: JsonData[];
   billingAlertRules: JsonData[];
+  costAnalysis?: JsonData | null;
 }
 
 // ============ 共享常量 ============