feat: 新增风险图谱算法与系统仪表盘及操作反馈体系

后端新增风险图谱算法模块、风险观察与反馈服务、规则 DSL
校验器和可解释性引擎，完善系统仪表盘和财务仪表盘统计，
优化 agent 运行和编排执行链路，清理旧开发文档，前端新增
系统趋势、负载热力图等多种仪表盘图表组件，完善操作反馈
对话框和工作台日期选择器，优化报销创建和审批详情交互，
补充单元测试覆盖。

web/src/utils/employeeProfileViewModel.js

@@ -46,6 +46,41 @@ const RADAR_COLORS = [
   '#db2777'
 ]
 
+const FINANCIAL_RADAR_CODES = [
+  'expense_intensity',
+  'application_rhythm',
+  'travel_entertainment',
+  'material_completeness',
+  'process_pressure'
+]
+
+const GOVERNANCE_RADAR_CODES = [
+  'ai_collaboration',
+  'approval_efficiency',
+  'approval_control'
+]
+
+export const USER_PROFILE_RADAR_VIEW_OPTIONS = [
+  {
+    value: 'financial_risk',
+    label: '财务风险视角',
+    shortLabel: '财务风险',
+    description: '费用、材料和流程相关维度'
+  },
+  {
+    value: 'collaboration_governance',
+    label: '协作治理视角',
+    shortLabel: '协作治理',
+    description: 'AI 协作和审批治理维度'
+  },
+  {
+    value: 'all_behavior',
+    label: '全部行为视角',
+    shortLabel: '全部行为',
+    description: '展示全部可用画像维度'
+  }
+]
+
 const TAG_ACCENT_COUNT = 8
 
 const SOURCE_LABELS = {
@@ -89,7 +124,7 @@ const JOB_TYPE_LABELS = {
   llm_wiki_sync: '知识库归纳同步',
   employee_behavior_profile_scan: '用户画像测算',
   workbench_on_demand: '工作台画像测算',
-  global_risk_scan: '全局风险巡检',
+  global_risk_scan: '财务风险图谱巡检',
   weekly_expense_report: '周费用报告'
 }
 
@@ -98,9 +133,7 @@ export function buildUserProfileMetricCards(profile, runs = [], currentUser = {}
   const aiMetrics = metricsOf(index.ai_usage)
   const userRuns = filterRunsByCurrentUser(runs, currentUser)
   const windowedUserRuns = filterRunsByProfileWindow(userRuns, profile)
-  const durationMs = hasProfileDurationMetric(aiMetrics)
-    ? resolveNumber(aiMetrics.ai_run_duration_ms)
-    : sumRunDurationMs(windowedUserRuns)
+  const durationMs = resolveUsageDurationMs(aiMetrics, windowedUserRuns)
   const durationDisplay = formatDurationMetric(durationMs)
   const commonAgent = resolveCommonAgent(windowedUserRuns)
   const tokenCount = resolveNumber(aiMetrics.exact_token_count) || resolveNumber(aiMetrics.estimated_token_count)
@@ -113,7 +146,7 @@ export function buildUserProfileMetricCards(profile, runs = [], currentUser = {}
       label: '使用时长',
       value: durationDisplay.value,
       unit: durationDisplay.unit,
-      hint: `近${resolveWindowDays(profile)}天智能体运行累计`,
+      hint: resolveUsageDurationHint(aiMetrics, profile),
       icon: 'mdi mdi-timer-sand',
       tone: 'primary'
     },
@@ -157,10 +190,12 @@ export function normalizeUserProfileTags(profile, limit = 8) {
       code: normalizeText(tag.code || tag.label),
       label: normalizeText(tag.label),
       displayLabel: normalizeText(tag.display_label || tag.displayLabel || tag.label),
+      category: normalizeCode(tag.category),
       tone: resolveTagTone(tag),
       score: clampScore(tag.score),
       reason: normalizeText(tag.reason) || '画像算法已识别该行为特征。',
-      confidence: resolveNumber(tag.confidence)
+      confidence: resolveNumber(tag.confidence),
+      radarDimensions: normalizeRadarDimensions(tag)
     }))
     .filter((tag) => tag.code && tag.displayLabel)
     .sort((left, right) => right.score - left.score)
@@ -194,6 +229,55 @@ export function normalizeUserProfileRadarDimensions(profile) {
   )
 }
 
+export function filterUserProfileRadarDimensions(dimensions, viewKey) {
+  const items = Array.isArray(dimensions) ? dimensions : []
+  const codes = resolveRadarViewCodes(viewKey)
+  if (!codes.length) {
+    return items
+  }
+
+  const filtered = items.filter((item) => codes.includes(normalizeCode(item?.code)))
+  return filtered.length ? filtered : items
+}
+
+export function filterUserProfileTagsByRadarView(tags, viewKey) {
+  const items = Array.isArray(tags) ? tags : []
+  const codes = resolveRadarViewCodes(viewKey)
+  if (!codes.length) {
+    return items
+  }
+
+  return items.filter((tag) => {
+    const dimensions = Array.isArray(tag?.radarDimensions) ? tag.radarDimensions : []
+    if (dimensions.some((code) => codes.includes(normalizeCode(code)))) {
+      return true
+    }
+    return resolveFallbackTagRadarCodes(tag).some((code) => codes.includes(code))
+  })
+}
+
+export function resolveUserProfileDefaultRadarView(profile) {
+  const profileTypes = new Set(
+    (Array.isArray(profile?.profiles) ? profile.profiles : [])
+      .map((item) => normalizeCode(item?.profile_type))
+      .filter(Boolean)
+  )
+  if (profileTypes.has('expense') || profileTypes.has('process_quality')) {
+    return 'financial_risk'
+  }
+  if (profileTypes.has('ai_usage') || profileTypes.has('approval')) {
+    return 'collaboration_governance'
+  }
+
+  const dimensions = normalizeUserProfileRadarDimensions(profile)
+  const financialScore = sumRadarScores(dimensions, FINANCIAL_RADAR_CODES)
+  const governanceScore = sumRadarScores(dimensions, GOVERNANCE_RADAR_CODES)
+  if (financialScore > 0 || governanceScore > 0) {
+    return financialScore >= governanceScore ? 'financial_risk' : 'collaboration_governance'
+  }
+  return 'all_behavior'
+}
+
 export function buildProfileOperationsFromAgentRuns(runs, currentUser, limit = 5) {
   const identities = resolveCurrentUserIdentities(currentUser)
   return (Array.isArray(runs) ? runs : [])
@@ -227,8 +311,69 @@ function metricsOf(profile) {
   return profile?.metrics && typeof profile.metrics === 'object' ? profile.metrics : {}
 }
 
+function resolveRadarViewCodes(viewKey) {
+  if (viewKey === 'financial_risk') {
+    return FINANCIAL_RADAR_CODES
+  }
+  if (viewKey === 'collaboration_governance') {
+    return GOVERNANCE_RADAR_CODES
+  }
+  return []
+}
+
+function resolveFallbackTagRadarCodes(tag) {
+  const category = normalizeCode(tag?.category)
+  if (['expense', 'travel', 'entertainment', 'process'].includes(category)) {
+    return FINANCIAL_RADAR_CODES
+  }
+  if (['ai', 'approval'].includes(category)) {
+    return GOVERNANCE_RADAR_CODES
+  }
+  return []
+}
+
+function normalizeRadarDimensions(tag) {
+  const dimensions = Array.isArray(tag?.radar_dimensions)
+    ? tag.radar_dimensions
+    : Array.isArray(tag?.radarDimensions)
+      ? tag.radarDimensions
+      : []
+  return dimensions.map((item) => normalizeCode(item)).filter(Boolean)
+}
+
+function sumRadarScores(dimensions, codes) {
+  const codeSet = new Set(codes)
+  return (Array.isArray(dimensions) ? dimensions : [])
+    .filter((item) => codeSet.has(normalizeCode(item?.code)))
+    .reduce((total, item) => total + clampScore(item?.score), 0)
+}
+
 function hasProfileDurationMetric(metrics) {
-  return Object.prototype.hasOwnProperty.call(metrics || {}, 'ai_run_duration_ms')
+  return (
+    Object.prototype.hasOwnProperty.call(metrics || {}, 'usage_duration_ms')
+    || Object.prototype.hasOwnProperty.call(metrics || {}, 'online_duration_ms')
+    || Object.prototype.hasOwnProperty.call(metrics || {}, 'ai_run_duration_ms')
+  )
+}
+
+function resolveUsageDurationMs(metrics, fallbackRuns) {
+  if (!hasProfileDurationMetric(metrics)) {
+    return sumRunDurationMs(fallbackRuns)
+  }
+  return resolveNumber(metrics.usage_duration_ms)
+    || resolveNumber(metrics.online_duration_ms)
+    || resolveNumber(metrics.ai_run_duration_ms)
+}
+
+function resolveUsageDurationHint(metrics, profile) {
+  const days = resolveWindowDays(profile)
+  if (normalizeCode(metrics?.usage_duration_mode) === 'online_session') {
+    return `近${days}天在线会话累计`
+  }
+  if (normalizeCode(metrics?.usage_duration_mode) === 'agent_run_fallback') {
+    return `近${days}天智能体运行累计`
+  }
+  return `近${days}天使用行为累计`
 }
 
 function filterRunsByCurrentUser(runs, currentUser) {