7989f3a159
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。
607 lines
18 KiB
JavaScript
607 lines
18 KiB
JavaScript
const PROFILE_TYPE_LABELS = {
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expense: '费用申请',
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process_quality: '流程质量',
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ai_usage: 'AI 协作',
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approval: '审核行为'
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}
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const STATUS_LABELS = {
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succeeded: '已完成',
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success: '已完成',
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running: '进行中',
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blocked: '待确认',
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failed: '失败'
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}
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const STATUS_TONES = {
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succeeded: 'success',
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success: 'success',
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running: 'warning',
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blocked: 'warning',
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failed: 'danger'
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}
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const AGENT_LABELS = {
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hermes: 'Hermes 数字员工',
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user_agent: '智能问答助手',
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orchestrator: '智能编排服务',
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system: '系统服务'
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}
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const AGENT_SHORT_LABELS = {
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hermes: 'Hermes',
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user_agent: '问答助手',
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orchestrator: '编排服务',
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system: '系统服务'
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}
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const RADAR_COLORS = [
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'#3a7ca5',
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'#0f9f8f',
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'#f59e0b',
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'#7c3aed',
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'#dc2626',
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'#2563eb',
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'#16a34a',
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'#db2777'
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]
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const FINANCIAL_RADAR_CODES = [
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'expense_intensity',
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'application_rhythm',
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'travel_entertainment',
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'material_completeness',
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'process_pressure'
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]
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const GOVERNANCE_RADAR_CODES = [
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'ai_collaboration',
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'approval_efficiency',
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'approval_control'
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]
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export const USER_PROFILE_RADAR_VIEW_OPTIONS = [
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{
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value: 'financial_risk',
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label: '财务风险视角',
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shortLabel: '财务风险',
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description: '费用、材料和流程相关维度'
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},
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{
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value: 'collaboration_governance',
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label: '协作治理视角',
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shortLabel: '协作治理',
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description: 'AI 协作和审批治理维度'
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},
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{
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value: 'all_behavior',
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label: '全部行为视角',
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shortLabel: '全部行为',
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description: '展示全部可用画像维度'
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}
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]
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const TAG_ACCENT_COUNT = 8
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const SOURCE_LABELS = {
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user_message: '用户对话',
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schedule: '定时任务',
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system_event: '系统事件',
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workbench: '个人工作台',
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detail: '单据详情',
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documents_application: '单据中心'
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}
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const SCENARIO_LABELS = {
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knowledge: '知识库问答',
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expense: '费用报销',
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reimbursement: '费用报销',
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expense_application: '费用申请',
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application: '费用申请',
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budget: '预算查询',
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audit: '风险审核',
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approval: '审批处理',
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policy: '制度问答',
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travel: '差旅费用',
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entertainment: '业务招待',
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accounts_receivable: '应收查询',
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accounts_payable: '应付查询'
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}
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const INTENT_LABELS = {
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query: '查询',
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explain: '解释',
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compare: '对比',
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risk_check: '风险检查',
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draft: '草稿生成',
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operate: '操作办理',
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review: '审核',
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submit: '提交'
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}
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const JOB_TYPE_LABELS = {
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knowledge_index_sync: '知识库索引同步',
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llm_wiki_sync: '知识库归纳同步',
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employee_behavior_profile_scan: '用户画像测算',
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workbench_on_demand: '工作台画像测算',
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global_risk_scan: '财务风险图谱巡检',
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weekly_expense_report: '周费用报告'
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}
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export function buildUserProfileMetricCards(profile, runs = [], currentUser = {}) {
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const index = indexProfiles(profile)
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const aiMetrics = metricsOf(index.ai_usage)
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const userRuns = filterRunsByCurrentUser(runs, currentUser)
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const windowedUserRuns = filterRunsByProfileWindow(userRuns, profile)
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const durationMs = resolveUsageDurationMs(aiMetrics, windowedUserRuns)
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const durationDisplay = formatDurationMetric(durationMs)
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const commonAgent = resolveCommonAgent(windowedUserRuns)
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const tokenCount = resolveNumber(aiMetrics.exact_token_count) || resolveNumber(aiMetrics.estimated_token_count)
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const tokenDisplay = formatTokenCount(tokenCount)
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const aiRunCount = resolveNumber(aiMetrics.ai_run_count) || windowedUserRuns.length
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return [
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{
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key: 'usage-duration',
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label: '使用时长',
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value: durationDisplay.value,
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unit: durationDisplay.unit,
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hint: resolveUsageDurationHint(aiMetrics, profile),
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icon: 'mdi mdi-timer-sand',
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tone: 'primary'
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},
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{
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key: 'common-agent',
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label: '常用智能体',
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value: commonAgent.label,
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unit: '',
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hint: commonAgent.count ? `${commonAgent.count} 次调用，占比 ${commonAgent.share}` : '暂无智能体调用记录',
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icon: 'mdi mdi-account-tie-voice-outline',
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tone: 'cyan'
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},
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{
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key: 'ai-usage',
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label: 'AI 使用次数',
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value: formatNumber(aiRunCount),
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unit: '次',
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hint: `近${resolveWindowDays(profile)}天智能协作记录`,
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icon: 'mdi mdi-robot-outline',
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tone: 'violet'
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},
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{
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key: 'token-usage',
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label: 'Token 消耗',
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value: tokenDisplay.value,
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unit: tokenDisplay.unit,
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hint: resolveTokenHint(aiMetrics),
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icon: 'mdi mdi-lightning-bolt-outline',
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tone: 'amber'
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}
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]
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}
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export function buildUserProfileSummaryMetrics(profile, runs = [], currentUser = {}) {
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return buildUserProfileMetricCards(profile, runs, currentUser).slice(0, 4)
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}
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export function normalizeUserProfileTags(profile, limit = 8) {
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return (Array.isArray(profile?.profile_tags) ? profile.profile_tags : [])
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.map((tag) => ({
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code: normalizeText(tag.code || tag.label),
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label: normalizeText(tag.label),
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displayLabel: normalizeText(tag.display_label || tag.displayLabel || tag.label),
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category: normalizeCode(tag.category),
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tone: resolveTagTone(tag),
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score: clampScore(tag.score),
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reason: normalizeText(tag.reason) || '画像算法已识别该行为特征。',
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confidence: resolveNumber(tag.confidence),
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radarDimensions: normalizeRadarDimensions(tag)
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}))
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.filter((tag) => tag.code && tag.displayLabel)
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.sort((left, right) => right.score - left.score)
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.slice(0, limit)
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.map((tag, index) => ({
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...tag,
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colorIndex: index % TAG_ACCENT_COUNT
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}))
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}
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export function normalizeUserProfileRadarDimensions(profile) {
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const dimensions = Array.isArray(profile?.radar?.dimensions) ? profile.radar.dimensions : []
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if (dimensions.length) {
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return withRadarColors(
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dimensions.map((item) => ({
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code: normalizeText(item.code || item.label),
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label: normalizeText(item.label || item.code),
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score: clampScore(item.score)
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}))
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)
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}
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return withRadarColors(
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(Array.isArray(profile?.profiles) ? profile.profiles : [])
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.map((item) => ({
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code: normalizeText(item.profile_type),
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label: PROFILE_TYPE_LABELS[item.profile_type] || normalizeText(item.profile_label || item.profile_type),
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score: clampScore(item.score)
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}))
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.filter((item) => item.code && item.label)
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)
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}
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export function filterUserProfileRadarDimensions(dimensions, viewKey) {
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const items = Array.isArray(dimensions) ? dimensions : []
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const codes = resolveRadarViewCodes(viewKey)
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if (!codes.length) {
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return items
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}
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const filtered = items.filter((item) => codes.includes(normalizeCode(item?.code)))
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return filtered.length ? filtered : items
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}
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export function filterUserProfileTagsByRadarView(tags, viewKey) {
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const items = Array.isArray(tags) ? tags : []
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const codes = resolveRadarViewCodes(viewKey)
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if (!codes.length) {
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return items
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}
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return items.filter((tag) => {
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const dimensions = Array.isArray(tag?.radarDimensions) ? tag.radarDimensions : []
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if (dimensions.some((code) => codes.includes(normalizeCode(code)))) {
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return true
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}
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return resolveFallbackTagRadarCodes(tag).some((code) => codes.includes(code))
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})
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}
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export function resolveUserProfileDefaultRadarView(profile) {
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const profileTypes = new Set(
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(Array.isArray(profile?.profiles) ? profile.profiles : [])
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.map((item) => normalizeCode(item?.profile_type))
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.filter(Boolean)
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)
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if (profileTypes.has('expense') || profileTypes.has('process_quality')) {
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return 'financial_risk'
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}
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if (profileTypes.has('ai_usage') || profileTypes.has('approval')) {
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return 'collaboration_governance'
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}
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const dimensions = normalizeUserProfileRadarDimensions(profile)
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const financialScore = sumRadarScores(dimensions, FINANCIAL_RADAR_CODES)
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const governanceScore = sumRadarScores(dimensions, GOVERNANCE_RADAR_CODES)
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if (financialScore > 0 || governanceScore > 0) {
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return financialScore >= governanceScore ? 'financial_risk' : 'collaboration_governance'
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}
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return 'all_behavior'
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}
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export function buildProfileOperationsFromAgentRuns(runs, currentUser, limit = 5) {
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const identities = resolveCurrentUserIdentities(currentUser)
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return (Array.isArray(runs) ? runs : [])
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.filter((run) => belongsToCurrentUser(run, identities))
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.sort((left, right) => Date.parse(right.started_at || 0) - Date.parse(left.started_at || 0))
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.slice(0, limit)
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.map((run, index) => ({
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id: normalizeText(run.run_id || run.id) || `operation-${index + 1}`,
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time: formatOperationTime(run.started_at),
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action: resolveOperationAction(run),
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target: resolveOperationTarget(run),
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channel: resolveOperationChannel(run),
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status: STATUS_LABELS[normalizeCode(run.status)] || normalizeText(run.status) || '未知',
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tone: STATUS_TONES[normalizeCode(run.status)] || 'info'
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}))
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}
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export function resolveCurrentUserProfileError(error) {
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return normalizeText(error?.message) || '用户画像读取失败，请稍后重试。'
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}
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function indexProfiles(profile) {
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return Object.fromEntries(
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(Array.isArray(profile?.profiles) ? profile.profiles : [])
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.map((item) => [normalizeText(item.profile_type), item])
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.filter(([key]) => key)
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)
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}
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function metricsOf(profile) {
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return profile?.metrics && typeof profile.metrics === 'object' ? profile.metrics : {}
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}
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function resolveRadarViewCodes(viewKey) {
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if (viewKey === 'financial_risk') {
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return FINANCIAL_RADAR_CODES
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}
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if (viewKey === 'collaboration_governance') {
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return GOVERNANCE_RADAR_CODES
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}
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return []
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}
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function resolveFallbackTagRadarCodes(tag) {
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const category = normalizeCode(tag?.category)
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if (['expense', 'travel', 'entertainment', 'process'].includes(category)) {
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return FINANCIAL_RADAR_CODES
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}
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if (['ai', 'approval'].includes(category)) {
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return GOVERNANCE_RADAR_CODES
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}
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return []
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}
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function normalizeRadarDimensions(tag) {
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const dimensions = Array.isArray(tag?.radar_dimensions)
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? tag.radar_dimensions
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: Array.isArray(tag?.radarDimensions)
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? tag.radarDimensions
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: []
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return dimensions.map((item) => normalizeCode(item)).filter(Boolean)
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}
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function sumRadarScores(dimensions, codes) {
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const codeSet = new Set(codes)
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return (Array.isArray(dimensions) ? dimensions : [])
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.filter((item) => codeSet.has(normalizeCode(item?.code)))
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.reduce((total, item) => total + clampScore(item?.score), 0)
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}
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function hasProfileDurationMetric(metrics) {
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return (
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Object.prototype.hasOwnProperty.call(metrics || {}, 'usage_duration_ms')
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|| Object.prototype.hasOwnProperty.call(metrics || {}, 'online_duration_ms')
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|| Object.prototype.hasOwnProperty.call(metrics || {}, 'ai_run_duration_ms')
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)
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}
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function resolveUsageDurationMs(metrics, fallbackRuns) {
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if (!hasProfileDurationMetric(metrics)) {
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return sumRunDurationMs(fallbackRuns)
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}
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return resolveNumber(metrics.usage_duration_ms)
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|| resolveNumber(metrics.online_duration_ms)
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|| resolveNumber(metrics.ai_run_duration_ms)
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}
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function resolveUsageDurationHint(metrics, profile) {
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const days = resolveWindowDays(profile)
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if (normalizeCode(metrics?.usage_duration_mode) === 'online_session') {
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return `近${days}天在线会话累计`
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}
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if (normalizeCode(metrics?.usage_duration_mode) === 'agent_run_fallback') {
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return `近${days}天智能体运行累计`
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}
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return `近${days}天使用行为累计`
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}
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function filterRunsByCurrentUser(runs, currentUser) {
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const identities = resolveCurrentUserIdentities(currentUser)
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return (Array.isArray(runs) ? runs : []).filter((run) => belongsToCurrentUser(run, identities))
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}
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function filterRunsByProfileWindow(runs, profile) {
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const cutoff = Date.now() - resolveWindowDays(profile) * 24 * 60 * 60 * 1000
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return (Array.isArray(runs) ? runs : []).filter((run) => {
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const startedAt = Date.parse(run?.started_at || '')
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return Number.isFinite(startedAt) && startedAt >= cutoff
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})
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}
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function belongsToCurrentUser(run, identities) {
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if (!identities.size) {
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return false
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}
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const userId = normalizeText(run?.user_id).toLowerCase()
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return Boolean(userId && identities.has(userId))
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}
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function resolveCurrentUserIdentities(user = {}) {
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return new Set(
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[
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user.username,
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user.email,
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user.name,
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user.employeeNo,
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user.employee_no
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]
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.map((item) => normalizeText(item).toLowerCase())
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.filter(Boolean)
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)
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}
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function resolveCommonAgent(runs) {
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const counts = new Map()
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for (const run of runs) {
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const code = normalizeCode(run?.agent || run?.route_json?.selected_agent || 'system') || 'system'
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counts.set(code, (counts.get(code) || 0) + 1)
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}
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const [code = '', count = 0] = Array.from(counts.entries())
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.sort((left, right) => right[1] - left[1])[0] || []
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if (!code || !count) {
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return { label: '暂无', count: 0, share: '0%' }
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}
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return {
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label: AGENT_SHORT_LABELS[code] || translateKnownValue(code, AGENT_LABELS, '智能体') || '智能体',
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count,
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share: formatPercent(count / Math.max(1, runs.length))
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}
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}
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function sumRunDurationMs(runs) {
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return runs.reduce((total, run) => total + resolveRunDurationMs(run), 0)
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}
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function resolveRunDurationMs(run) {
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const startedAt = Date.parse(run?.started_at || '')
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const finishedAt = Date.parse(run?.finished_at || '')
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if (Number.isFinite(startedAt) && Number.isFinite(finishedAt) && finishedAt > startedAt) {
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return Math.min(finishedAt - startedAt, 24 * 60 * 60 * 1000)
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}
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return (Array.isArray(run?.tool_calls) ? run.tool_calls : []).reduce(
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(total, tool) => total + Math.max(0, resolveNumber(tool?.duration_ms)),
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0
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)
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}
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function resolveOperationAction(run) {
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const semanticText = normalizeText(run?.semantic_parse?.raw_query)
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if (semanticText) {
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return `${resolveOperationBusinessLabel(run)}：${semanticText}`
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}
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return translateKnownValue(run?.result_summary, JOB_TYPE_LABELS, '')
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|| translateKnownValue(run?.route_json?.job_type, JOB_TYPE_LABELS, '执行系统任务')
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|| '执行智能财务任务'
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}
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function resolveOperationTarget(run) {
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return translateKnownValue(run?.route_json?.task_title, JOB_TYPE_LABELS, '')
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|| translateKnownValue(run?.route_json?.asset_name, JOB_TYPE_LABELS, '')
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|| translateKnownValue(run?.semantic_parse?.scenario, SCENARIO_LABELS, '业务操作')
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|| translateKnownValue(run?.task_id, JOB_TYPE_LABELS, '系统任务')
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|| '个人工作台'
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}
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function resolveOperationChannel(run) {
|
||
const agent = translateKnownValue(run?.agent, AGENT_LABELS, '智能服务') || 'Hermes 数字员工'
|
||
const source = translateKnownValue(run?.source, SOURCE_LABELS, '系统入口')
|
||
return source ? `${agent} · ${source}` : agent
|
||
}
|
||
|
||
function resolveOperationBusinessLabel(run) {
|
||
const scenario = translateKnownValue(run?.semantic_parse?.scenario, SCENARIO_LABELS, '业务操作')
|
||
const intent = translateKnownValue(run?.semantic_parse?.intent, INTENT_LABELS, '')
|
||
if (scenario && intent) {
|
||
return `${scenario}${intent}`
|
||
}
|
||
return scenario || intent || '发起'
|
||
}
|
||
|
||
function resolveTagTone(tag) {
|
||
const polarity = normalizeText(tag?.polarity || tag?.tone).toLowerCase()
|
||
if (['risk', 'danger', 'negative'].includes(polarity)) {
|
||
return 'risk'
|
||
}
|
||
if (['positive', 'success'].includes(polarity)) {
|
||
return 'positive'
|
||
}
|
||
return 'behavior'
|
||
}
|
||
|
||
function resolveWindowDays(profile) {
|
||
const days = Number(profile?.window_days || 90)
|
||
return Number.isFinite(days) && days > 0 ? Math.round(days) : 90
|
||
}
|
||
|
||
function resolveTokenHint(metrics) {
|
||
const mode = normalizeText(metrics.token_count_mode)
|
||
return mode === 'estimated_token_count' ? '按运行载荷估算' : '模型调用累计'
|
||
}
|
||
|
||
function formatTokenCount(value) {
|
||
const count = resolveNumber(value)
|
||
if (count >= 10000) {
|
||
return { value: trimNumber(count / 10000, 2), unit: '万' }
|
||
}
|
||
return { value: formatNumber(count), unit: 'tokens' }
|
||
}
|
||
|
||
function formatDurationMetric(totalMs) {
|
||
const seconds = Math.round(Math.max(0, resolveNumber(totalMs)) / 1000)
|
||
if (seconds < 60) {
|
||
return { value: formatNumber(seconds), unit: '秒' }
|
||
}
|
||
const minutes = seconds / 60
|
||
if (minutes < 60) {
|
||
return { value: trimNumber(minutes, minutes >= 10 ? 0 : 1), unit: '分钟' }
|
||
}
|
||
const hours = minutes / 60
|
||
return { value: trimNumber(hours, hours >= 10 ? 0 : 1), unit: '小时' }
|
||
}
|
||
|
||
function withRadarColors(items) {
|
||
return items.map((item, index) => ({
|
||
...item,
|
||
color: item.color || RADAR_COLORS[index % RADAR_COLORS.length]
|
||
}))
|
||
}
|
||
|
||
function formatOperationTime(value) {
|
||
const date = new Date(value)
|
||
if (Number.isNaN(date.getTime())) {
|
||
return '时间未知'
|
||
}
|
||
const now = new Date()
|
||
const sameDay = date.toDateString() === now.toDateString()
|
||
const yesterday = new Date(now)
|
||
yesterday.setDate(now.getDate() - 1)
|
||
const time = `${pad(date.getHours())}:${pad(date.getMinutes())}`
|
||
if (sameDay) {
|
||
return `今天 ${time}`
|
||
}
|
||
if (date.toDateString() === yesterday.toDateString()) {
|
||
return `昨天 ${time}`
|
||
}
|
||
return `${pad(date.getMonth() + 1)}-${pad(date.getDate())} ${time}`
|
||
}
|
||
|
||
function formatNumber(value) {
|
||
return String(Math.round(resolveNumber(value)))
|
||
}
|
||
|
||
function formatPercent(value) {
|
||
return `${Math.round(resolveNumber(value) * 100)}%`
|
||
}
|
||
|
||
function formatMoney(value) {
|
||
return `¥${trimNumber(resolveNumber(value), 2)}`
|
||
}
|
||
|
||
function trimNumber(value, digits = 0) {
|
||
const number = Number(value || 0)
|
||
return number.toFixed(digits).replace(/\.0+$/, '').replace(/(\.\d*?)0+$/, '$1')
|
||
}
|
||
|
||
function clampScore(value) {
|
||
const score = Math.round(resolveNumber(value))
|
||
return Math.max(0, Math.min(100, score))
|
||
}
|
||
|
||
function resolveNumber(value) {
|
||
const number = Number(value || 0)
|
||
return Number.isFinite(number) ? number : 0
|
||
}
|
||
|
||
function normalizeText(value) {
|
||
return String(value || '').trim()
|
||
}
|
||
|
||
function normalizeCode(value) {
|
||
return normalizeText(value).toLowerCase()
|
||
}
|
||
|
||
function translateKnownValue(value, labels, internalFallback = '') {
|
||
const raw = normalizeText(value)
|
||
if (!raw) {
|
||
return ''
|
||
}
|
||
const mapped = labels[normalizeCode(raw)]
|
||
if (mapped) {
|
||
return mapped
|
||
}
|
||
return isInternalCode(raw) ? internalFallback : raw
|
||
}
|
||
|
||
function isInternalCode(value) {
|
||
return /^[a-z][a-z0-9_:-]*$/i.test(normalizeText(value))
|
||
}
|
||
|
||
function pad(value) {
|
||
return String(value).padStart(2, '0')
|
||
}
|