refactor(ai-chat): 拆分超大文件并通过 aislop 100 分门槛
- AiChatService 拆出抽象基类，职责不变 - submissions 按提交内容/评审确认/运行时/流程拆为 4 个模块并保持导出兼容 - 导入工具执行器抽取共享 runner，消除重复签名块 - 全仓 aislop 扫描 100/100，0 警告
This commit is contained in:
325
apps/server/src/ai-chat/ai-chat.tool-actions.import.ts
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325
apps/server/src/ai-chat/ai-chat.tool-actions.import.ts
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import {
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IMPORT_STEP_KEYS,
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type ImportStageRequest,
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type ImportStepKey,
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type PreflightReport,
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} from '../imports/imports.types';
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import { permittedStepKeys } from '../imports/imports.access';
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import type { AiChatServiceContext, AiSseEmitter, ModelToolCall } from './ai-chat.types';
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import type { AgentToolContext } from './ai-chat.tools';
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import { AiMessage } from './entities';
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import { finishToolRun, startToolRun } from './ai-chat.tools';
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import {
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isExcelAttachment,
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parseConfirmedMapping,
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parseConfirmedSettings,
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} from './ai-chat.import-confirm';
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function parseAttachmentArgs(
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parsedArgs: unknown,
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): { parsedRecord: Record<string, unknown>; attachmentId: number } {
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const parsedRecord =
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parsedArgs && typeof parsedArgs === 'object' && !Array.isArray(parsedArgs)
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? (parsedArgs as Record<string, unknown>)
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: {};
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if (
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typeof parsedRecord.attachmentId !== 'number' ||
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!Number.isInteger(parsedRecord.attachmentId) ||
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parsedRecord.attachmentId <= 0
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) {
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throw new Error('缺少附件 attachmentId');
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}
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return { parsedRecord, attachmentId: parsedRecord.attachmentId };
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}
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async function beginImportToolRun(
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context: AiChatServiceContext,
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messageId: number,
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call: ModelToolCall,
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emit: AiSseEmitter,
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toolName: string,
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) {
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return startToolRun(context, messageId, call, emit, {
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toolName,
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skillKey: null,
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argumentsData: null,
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});
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}
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interface ImportToolContext {
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run: Awaited<ReturnType<typeof beginImportToolRun>>['run'];
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parsedArgs: Awaited<ReturnType<typeof beginImportToolRun>>['parsedArgs'];
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startedAt: Awaited<ReturnType<typeof beginImportToolRun>>['startedAt'];
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assistant: AiMessage;
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agentContext: AgentToolContext;
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context: AiChatServiceContext;
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call: ModelToolCall;
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emit: AiSseEmitter;
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messageId: number;
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}
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async function runImportTool(
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context: AiChatServiceContext,
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messageId: number,
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call: ModelToolCall,
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agentContext: AgentToolContext,
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emit: AiSseEmitter,
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toolName: string,
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handler: (tool: ImportToolContext) => Promise<string>,
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): Promise<string> {
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const { run, parsedArgs, startedAt } = await beginImportToolRun(
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context,
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messageId,
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call,
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emit,
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toolName,
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);
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try {
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const assistant = await context.messages.findOne({ where: { id: messageId } });
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if (!assistant) throw new Error('assistant message missing');
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return await handler({ run, parsedArgs, startedAt, assistant, agentContext, context, call, emit, messageId });
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} catch (error) {
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const summary = error instanceof Error ? error.message.slice(0, 100) : `${toolName} 失败`;
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await finishToolRun(context, run, call, startedAt, {
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status: 'failed',
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summary,
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error: summary,
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}, emit);
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return JSON.stringify({ status: 'failed', error: run.resultSummary });
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}
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}
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type ImportToolExecutor = (
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context: AiChatServiceContext,
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messageId: number,
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call: ModelToolCall,
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agentContext: AgentToolContext,
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emit: AiSseEmitter,
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) => Promise<string>;
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function makeImportToolExecutor(
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toolName: 'preflight_import' | 'start_import_wizard',
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handler: (tool: ImportToolContext) => Promise<string>,
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): ImportToolExecutor {
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return (context, messageId, call, agentContext, emit) =>
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runImportTool(context, messageId, call, agentContext, emit, toolName, handler);
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}
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export const executePreflightImport = makeImportToolExecutor(
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'preflight_import',
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async ({ run, parsedArgs, startedAt, assistant, agentContext: ac, context, call, emit, messageId }) => {
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const { parsedRecord, attachmentId } = parseAttachmentArgs(parsedArgs);
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const headerRow =
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parsedRecord.headerRow === undefined ? 1 : Number(parsedRecord.headerRow);
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if (!Number.isInteger(headerRow) || headerRow < 1 || headerRow > 1000) {
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throw new Error('headerRow 必须是 1-1000 之间的整数');
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}
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const [attachment] = await context.attachmentService.requireReadyOwned(ac.userId, [
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attachmentId as number,
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]);
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if (!isExcelAttachment(attachment)) {
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throw new Error('附件不是 Excel 文件，无法预检导入');
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}
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if (!context.importsService) throw new Error('导入预检服务未配置');
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const buffer = await context.attachmentService.readStoredBuffer(attachment);
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const preflight: PreflightReport = await context.importsService.preflightFile({
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originalName: attachment.originalName,
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mimeType: attachment.mimeType,
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size: attachment.size,
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buffer,
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}, headerRow);
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const permittedSteps = permittedStepKeys({
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id: ac.userId,
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permissions: [...ac.permissions],
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isSuperAdmin: ac.isSuperAdmin,
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});
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const preflightCard: PreflightReport = {
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...preflight,
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attachmentId: attachment.id,
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headerRow,
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permittedSteps,
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resolved: false,
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runId: null,
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};
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assistant.metadata = {
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...assistant.metadata,
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a2uiImportPreflight: preflightCard,
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};
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await context.messages.save(assistant);
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await finishToolRun(context, run, call, startedAt, {
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status: 'success',
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summary: `已完成导入预检：${preflight.stages
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.map((stage) => `${stage.label} ${stage.total} 行`)
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.join('、') || '未识别到可导入阶段'}`,
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}, emit);
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emit('ui.import_preflight', { messageId, preflight: preflightCard });
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return preflightModelPayload(preflight, permittedSteps);
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});
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export const executeStartImportWizard = makeImportToolExecutor(
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'start_import_wizard',
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async ({ run, parsedArgs, startedAt, assistant, agentContext: ac, context, call, emit, messageId }) => {
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const { parsedRecord, attachmentId } = parseAttachmentArgs(parsedArgs);
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const [attachment] = await context.attachmentService.requireReadyOwned(ac.userId, [
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attachmentId as number,
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]);
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if (!isExcelAttachment(attachment)) throw new Error('附件不是 Excel 文件，无法生成导入向导');
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const stages = Array.isArray(parsedRecord.stages)
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? (parsedRecord.stages as ImportStageRequest[])
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: [];
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if (stages.length === 0) throw new Error('缺少 stages 参数');
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for (const stage of stages) {
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if (!IMPORT_STEP_KEYS.includes(stage.stepKey)) {
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throw new Error(`stages 包含未知业务类型：${String(stage.stepKey)}`);
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}
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if (!stage.sheet || !String(stage.sheet).trim()) {
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throw new Error(`stages 中「${stage.stepKey}」缺少工作表 sheet，请指定 Excel 中对应的 sheet 名`);
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}
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if (
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stage.headerRow !== undefined &&
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(!Number.isInteger(stage.headerRow) || stage.headerRow < 1 || stage.headerRow > 1000)
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) {
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throw new Error(`stages 中「${stage.stepKey}」的 headerRow 必须是 1-1000 之间的整数`);
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}
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}
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const mapping = parseConfirmedMapping(parsedRecord.mapping);
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const settings = parseConfirmedSettings(parsedRecord);
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if (!context.importsService) throw new Error('导入向导服务未配置');
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const buffer = await context.attachmentService.readStoredBuffer(attachment);
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const detail = await context.importsService.createRun(
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{
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id: ac.userId,
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permissions: [...ac.permissions],
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isSuperAdmin: ac.isSuperAdmin,
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},
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'ai',
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{
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originalName: attachment.originalName,
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mimeType: attachment.mimeType,
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size: attachment.size,
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buffer,
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},
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assistant.conversationId,
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stages,
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mapping,
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settings,
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);
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const wizard = compactImportWizard(detail);
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const preflightMeta = assistant.metadata?.a2uiImportPreflight;
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assistant.metadata = {
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...assistant.metadata,
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...(preflightMeta && typeof preflightMeta === 'object' && !Array.isArray(preflightMeta)
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? {
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a2uiImportPreflight: {
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...(preflightMeta as Record<string, unknown>),
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resolved: true,
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runId: detail.id,
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},
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}
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: {}),
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a2uiImportWizard: wizard,
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};
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await context.messages.save(assistant);
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await finishToolRun(context, run, call, startedAt, {
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status: 'success',
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summary: `已生成导入向导：${detail.steps
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.filter((step) => step.status !== 'skipped')
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.map((step) => step.label)
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.join('、')}`,
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}, emit);
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if (preflightMeta && typeof preflightMeta === 'object' && !Array.isArray(preflightMeta)) {
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emit('ui.import_preflight', {
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messageId,
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preflight: {
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...(preflightMeta as Record<string, unknown>),
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resolved: true,
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runId: detail.id,
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},
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});
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}
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emit('ui.import_wizard', { messageId, wizard });
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return JSON.stringify({
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status: 'success',
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runId: detail.id,
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steps: detail.steps
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.filter((step) => step.status !== 'skipped')
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.map((step) => ({ stepKey: step.stepKey, label: step.label, sheets: step.sheets })),
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permittedSteps: permittedStepKeys({
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id: ac.userId,
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permissions: [...ac.permissions],
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isSuperAdmin: ac.isSuperAdmin,
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}),
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message: '导入向导已生成，请提示用户打开向导，按阶段预览并确认后系统才会入库',
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});
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});
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function preflightModelPayload(
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report: PreflightReport,
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permittedSteps: ImportStepKey[],
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): string {
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const guidance =
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'预检报告已以卡片展示：请引导用户在卡内确认列映射与策略并点击「生成导入向导」；' +
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'仅当用户在聊天文本中显式给出确认时才调用 start_import_wizard';
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const fullPayload = JSON.stringify({
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status: 'success',
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report,
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permittedSteps,
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message: guidance,
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});
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if (fullPayload.length <= 32 * 1024) return fullPayload;
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return JSON.stringify({
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status: 'success',
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truncated: true,
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report: {
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verdict: report.verdict,
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stages: report.stages.map((stage) => ({
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stepKey: stage.stepKey,
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label: stage.label,
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sheetNames: stage.sheetNames,
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total: stage.total,
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create: stage.create,
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update: stage.update,
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error: stage.error,
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skip: stage.skip,
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mapping: stage.mapping,
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missingRequired: stage.missingRequired,
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})),
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questions: report.questions,
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errorSamples: report.errorSamples.slice(0, 10),
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nextSteps: report.nextSteps,
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},
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permittedSteps,
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message: guidance,
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});
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}
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export function compactImportWizard(detail: any): {
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runId: string;
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fileName: string;
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sheets: Array<{
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name: string;
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suggestedStepKey: string | null;
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headers: string[];
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rowCount: number;
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}>;
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steps: Array<{ stepKey: string; label: string; sheets: string[]; status: string }>;
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} {
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return {
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runId: detail.id,
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fileName: detail.fileName,
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sheets: detail.sheets.map((sheet: any) => ({
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name: sheet.name,
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suggestedStepKey: sheet.suggestedStepKey,
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headers: sheet.headers,
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rowCount: sheet.rowCount,
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})),
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steps: detail.steps.map((step: any) => ({
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stepKey: step.stepKey,
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label: step.label,
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sheets: step.sheets,
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status: step.status,
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})),
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};
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}
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