278 lines
11 KiB
JavaScript
278 lines
11 KiB
JavaScript
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import { isReimbursementCreationIntent } from './workbenchAiApplicationGateModel.js'
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import {
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buildRuleFallbackWorkbenchAiIntentPlan,
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isLowConfidenceTravelApplicationPlan,
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normalizeWorkbenchAiIntentPlan,
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resolveExecutableTravelApplicationPlan
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} from './workbenchAiIntentPlannerModel.js'
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import {
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buildInitialModelPlanningThinkingEvents,
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buildModelPlanningProgressSchedule,
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mergeWorkbenchAiThinkingEvents
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} from './workbenchAiPlanningThinkingModel.js'
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export function useWorkbenchAiIntentExecution(options) {
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const {
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actionRouter,
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activeConversationTitle,
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activateInlineConversation,
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applicationFlow,
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assistantDraft,
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clearAiModeFiles,
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closeWorkbenchDatePicker,
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conversationId,
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conversationMessages,
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createInlineMessage,
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expenseFlow,
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inlineConversationAutoScrollPinned,
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persistCurrentConversation,
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removeWorkbenchDateTag,
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replaceInlineMessage,
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resolveInlineThinkingEvents,
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scrollInlineConversationToBottom,
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searchConversationId,
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sending,
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stewardFlow
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} = options
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function isModelPlannedReimbursementTask(modelPlan = {}) {
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const tasks = Array.isArray(modelPlan?.tasks) ? modelPlan.tasks : []
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return tasks.some((task) => {
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const taskType = String(task?.task_type || task?.taskType || '').trim()
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const assignedAgent = String(task?.assigned_agent || task?.assignedAgent || '').trim()
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return taskType === 'reimbursement' || assignedAgent === 'reimbursement_assistant'
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})
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}
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function updateModelPlanningThinkingEvent(messageId, event) {
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const message = conversationMessages.value.find((item) => item.id === messageId)
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if (!message) {
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return
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}
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const currentPlan = message.stewardPlan || {}
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message.stewardPlan = {
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...currentPlan,
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streamStatus: 'streaming',
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thinkingEvents: mergeWorkbenchAiThinkingEvents(resolveInlineThinkingEvents(message), [event])
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}
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persistCurrentConversation()
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scrollInlineConversationToBottom({ force: inlineConversationAutoScrollPinned.value })
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}
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function startModelPlanningProgressUpdates(messageId) {
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const timerIds = buildModelPlanningProgressSchedule().map(({ delayMs, event }) => (
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globalThis.setTimeout(() => {
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updateModelPlanningThinkingEvent(messageId, event)
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}, delayMs)
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))
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return () => {
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timerIds.forEach((timerId) => globalThis.clearTimeout(timerId))
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}
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}
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function startModelPlanningConversation(cleanPrompt, entry = {}) {
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if (conversationId.value === searchConversationId) {
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conversationId.value = ''
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conversationMessages.value = []
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activeConversationTitle.value = ''
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}
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activateInlineConversation({
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title: entry.label || cleanPrompt.slice(0, 18) || '新对话'
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})
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inlineConversationAutoScrollPinned.value = true
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conversationMessages.value.push(createInlineMessage('user', cleanPrompt))
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assistantDraft.value = ''
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removeWorkbenchDateTag()
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closeWorkbenchDatePicker()
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clearAiModeFiles()
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const pendingMessage = createInlineMessage('assistant', '正在识别意图，准备拆解申请、报销和附件任务。', {
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pending: true,
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stewardPlan: {
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streamStatus: 'streaming',
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thinkingEvents: buildInitialModelPlanningThinkingEvents()
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}
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})
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conversationMessages.value.push(pendingMessage)
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scrollInlineConversationToBottom()
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persistCurrentConversation()
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return pendingMessage
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}
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function buildModelPlannedNextTaskAction(remainingTasks = []) {
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const tasks = Array.isArray(remainingTasks) ? remainingTasks : []
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const nextTask = tasks[0]
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if (!nextTask || typeof nextTask !== 'object') {
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return null
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}
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const taskType = String(nextTask.task_type || nextTask.taskType || '').trim()
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const assignedAgent = String(nextTask.assigned_agent || nextTask.assignedAgent || '').trim()
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const isApplication = taskType === 'expense_application' || assignedAgent === 'application_assistant'
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const isReimbursement = taskType === 'reimbursement' || assignedAgent === 'reimbursement_assistant'
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if (!isApplication && !isReimbursement) {
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return null
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}
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const ontologyFields = nextTask.ontology_fields || nextTask.ontologyFields || {}
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const flowId = isApplication ? 'travel_application' : 'travel_reimbursement'
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const taskLabel = isApplication ? '出差申请' : '费用报销'
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return {
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label: `继续处理${taskLabel}`,
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action_type: 'steward_continue_next_task',
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payload: {
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steward_confirm_flow: true,
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flow_id: flowId,
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steward_current_task: nextTask,
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expense_type: String(ontologyFields.expense_type || 'travel').trim() || 'travel',
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expense_type_label: String(ontologyFields.expense_type_label || '差旅费').trim() || '差旅费',
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ontology_fields: ontologyFields,
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original_message: String(nextTask.summary || nextTask.title || `继续处理${taskLabel}`).trim(),
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steward_remaining_tasks: tasks.slice(1)
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}
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}
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}
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function startModelPlannedNextTask(remainingTasks = []) {
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const nextTaskAction = buildModelPlannedNextTaskAction(remainingTasks)
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if (nextTaskAction) {
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actionRouter.handleInlineSuggestedAction(nextTaskAction)
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}
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}
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function startModelPlannedApplicationPreview(travelApplicationRequest, plannerPendingMessage = null) {
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void applicationFlow.startAiApplicationPreview(
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travelApplicationRequest.expenseType,
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travelApplicationRequest.expenseTypeLabel,
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travelApplicationRequest.sourceText,
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{
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userMessage: travelApplicationRequest.sourceText,
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pushUserMessage: !plannerPendingMessage,
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pendingMessageId: plannerPendingMessage?.id,
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ontologyFields: travelApplicationRequest.ontologyFields,
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autoSubmit: travelApplicationRequest.autoSubmit,
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autoSaveDraft: travelApplicationRequest.autoSaveDraft,
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requestedSubmit: travelApplicationRequest.requestedSubmit,
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submitRequiresConfirmation: travelApplicationRequest.submitRequiresConfirmation,
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stewardRemainingTasks: travelApplicationRequest.stewardRemainingTasks,
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onPreviewReadyForNextTask: startModelPlannedNextTask,
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onApplicationActionCompleted: startModelPlannedNextTask
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}
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)
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}
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function buildLowConfidenceTravelApplicationConfirmationText(request, plan) {
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const fields = request.ontologyFields || {}
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const summaryParts = []
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if (fields.time_range) summaryParts.push(`时间：${fields.time_range}`)
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if (fields.location) summaryParts.push(`地点：${fields.location}`)
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if (fields.reason) summaryParts.push(`事由：${fields.reason}`)
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if (fields.transport_mode) summaryParts.push(`交通：${fields.transport_mode}`)
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const summary = summaryParts.length ? `\n\n${summaryParts.join('；')}` : ''
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const confidenceNote = Number.isFinite(Number(plan?.confidence))
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? `（模型识别置信度较低，约 ${Math.round(Number(plan.confidence) * 100)}%）`
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: '（模型识别置信度较低）'
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return [
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'### 需要确认：您是要发起出差申请吗？',
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'',
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`小财管家把这句话理解成了“发起差旅申请”${confidenceNote}，为避免误操作，先请您确认。`,
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summary,
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'',
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'点击下方「确认发起出差申请」即可继续；如果理解有误，请补充说明您的实际需求。'
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].filter(Boolean).join('\n')
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}
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function startModelPlannedTravelApplicationConfirmation(travelApplicationRequest, plan, plannerPendingMessage) {
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const confirmAction = {
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label: '确认发起出差申请',
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description: '根据上面识别到的信息生成出差申请预览。',
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icon: 'mdi mdi-check-circle-outline',
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action_type: 'ai_application_confirm_intent',
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payload: {
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ontologyFields: travelApplicationRequest.ontologyFields,
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sourceText: travelApplicationRequest.sourceText,
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autoSubmit: travelApplicationRequest.autoSubmit,
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autoSaveDraft: travelApplicationRequest.autoSaveDraft,
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requestedSubmit: travelApplicationRequest.requestedSubmit,
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submitRequiresConfirmation: travelApplicationRequest.submitRequiresConfirmation,
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stewardRemainingTasks: travelApplicationRequest.stewardRemainingTasks
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}
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}
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replaceInlineMessage(plannerPendingMessage.id, createInlineMessage(
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'assistant',
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buildLowConfidenceTravelApplicationConfirmationText(travelApplicationRequest, plan),
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{
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id: plannerPendingMessage.id,
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suggestedActions: [confirmAction],
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stewardPlan: {
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streamStatus: 'completed',
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thinkingEvents: resolveInlineThinkingEvents(plannerPendingMessage)
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.map((item) => ({ ...item, status: 'completed' }))
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}
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}
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))
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persistCurrentConversation()
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scrollInlineConversationToBottom({ force: inlineConversationAutoScrollPinned.value })
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}
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async function executeModelPlannedWorkbenchIntent(cleanPrompt, entry = {}, files = []) {
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let intentPlan = null
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let modelPlan = null
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const plannerPendingMessage = startModelPlanningConversation(cleanPrompt, entry)
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const stopPlanningProgressUpdates = startModelPlanningProgressUpdates(plannerPendingMessage.id)
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sending.value = true
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try {
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modelPlan = await stewardFlow.resolveInlineExecutionPlan(cleanPrompt, entry, files, {
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pendingMessageId: plannerPendingMessage.id
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})
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intentPlan = normalizeWorkbenchAiIntentPlan(modelPlan, { prompt: cleanPrompt })
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} catch (error) {
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console.warn('AI mode intent planner failed, using local fallback:', error)
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const ruleRequest = resolveExecutableTravelApplicationPlan(
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buildRuleFallbackWorkbenchAiIntentPlan(cleanPrompt)
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)
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if (ruleRequest) {
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sending.value = false
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startModelPlannedApplicationPreview(ruleRequest, plannerPendingMessage)
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return
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}
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} finally {
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stopPlanningProgressUpdates()
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sending.value = false
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}
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const travelApplicationRequest = resolveExecutableTravelApplicationPlan(intentPlan)
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if (travelApplicationRequest) {
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if (isLowConfidenceTravelApplicationPlan(intentPlan)) {
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startModelPlannedTravelApplicationConfirmation(travelApplicationRequest, intentPlan, plannerPendingMessage)
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} else {
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startModelPlannedApplicationPreview(travelApplicationRequest, plannerPendingMessage)
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}
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return
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}
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if (isModelPlannedReimbursementTask(modelPlan) || isReimbursementCreationIntent(cleanPrompt)) {
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replaceInlineMessage(plannerPendingMessage.id, createInlineMessage(
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'assistant',
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'已识别为报销任务，正在进入报销流程。',
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{
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id: plannerPendingMessage.id,
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stewardPlan: {
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streamStatus: 'completed',
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thinkingEvents: resolveInlineThinkingEvents(plannerPendingMessage)
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.map((item) => ({ ...item, status: 'completed' }))
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}
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}
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))
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void expenseFlow.startAiReimbursementAssociationGate(cleanPrompt, entry.label || cleanPrompt)
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return
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}
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void stewardFlow.requestInlineAssistantReply(cleanPrompt, entry, files, {
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pendingMessageId: plannerPendingMessage.id
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})
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}
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return {
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executeModelPlannedWorkbenchIntent,
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startModelPlannedNextTask
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}
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}
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