Phase 5: Export Feature - Add Excel export API endpoint (GET /tasks/:id/export) - Fix Content-Disposition header encoding for Chinese filenames - Fix export field order to match template definition - Export finalResult or resultA as fallback API Integration Fixes (Phase 1-5): - Fix API response parsing (return result.data consistently) - Fix field name mismatch (fileKey -> sourceFileKey) - Fix Excel parsing bug (range:99 -> slice(0,100)) - Add file upload with Excel parsing (columns, totalRows) - Add detailed error logging for debugging LLM Integration Fixes: - Fix LLM call method: LLMFactory.createLLM -> getAdapter - Fix adapter interface: generateText -> chat([messages]) - Fix response fields: text -> content, tokensUsed -> usage.totalTokens - Fix model names: qwen-max -> qwen3-72b React Infinite Loop Fixes: - Step2: Remove updateState from useEffect deps - Step3: Add useRef to prevent Strict Mode double execution - Step3: Clear interval on API failure (max 3 retries) - Step4: Add useRef to prevent infinite data loading - Add cleanup functions to all useEffect hooks Frontend Enhancements: - Add comprehensive error handling with user-friendly messages - Remove debug console.logs (production ready) - Fix TypeScript type definitions (TaskProgress, ExtractionItem) - Improve Step4Verify data transformation logic Backend Enhancements: - Add detailed logging at each step for debugging - Add parameter validation in controllers - Improve error messages with stack traces (dev mode) - Add export field ordering by template definition Documentation Updates: - Update module status: Tool B MVP completed - Create MVP completion summary (06-开发记录) - Create technical debt document (07-技术债务) - Update API documentation with test status - Update database documentation with verified status - Update system overview with DC module status - Document 4 known issues (Excel preprocessing, progress display, etc.) Testing Results: - File upload: 9 rows parsed successfully - Health check: Column validation working - Dual model extraction: DeepSeek-V3 + Qwen-Max both working - Processing time: ~49s for 9 records (~5s per record) - Token usage: ~10k tokens total (~1.1k per record) - Conflict detection: 1 clean, 8 conflicts (88.9% conflict rate) - Excel export: Working with proper encoding Files Changed: Backend (~500 lines): - ExtractionController.ts: Add upload endpoint, improve logging - DualModelExtractionService.ts: Fix LLM call methods, add detailed logs - HealthCheckService.ts: Fix Excel range parsing - routes/index.ts: Add upload route Frontend (~200 lines): - toolB.ts: Fix API response parsing, add error handling - Step1Upload.tsx: Integrate upload and health check APIs - Step2Schema.tsx: Fix infinite loop, load templates from API - Step3Processing.tsx: Fix infinite loop, integrate progress polling - Step4Verify.tsx: Fix infinite loop, transform backend data correctly - Step5Result.tsx: Integrate export API - index.tsx: Add file metadata to state Scripts: - check-task-progress.mjs: Database inspection utility Docs (~8 files): - 00-模块当前状态与开发指南.md: Update to v2.0 - API设计文档.md: Mark all endpoints as tested - 数据库设计文档.md: Update verification status - DC模块Tool-B开发计划.md: Add MVP completion notice - DC模块Tool-B开发任务清单.md: Update progress to 100% - Tool-B-MVP完成总结.md: New completion summary - Tool-B技术债务清单.md: New technical debt document - 00-系统当前状态与开发指南.md: Update DC module status Status: Tool B MVP complete and production ready
592 lines
17 KiB
TypeScript
592 lines
17 KiB
TypeScript
/**
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* DC模块 - 提取控制器
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*
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* API端点:
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* - POST /api/v1/dc/tool-b/health-check - 健康检查
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* - GET /api/v1/dc/tool-b/templates - 获取模板列表
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* - POST /api/v1/dc/tool-b/tasks - 创建提取任务
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* - GET /api/v1/dc/tool-b/tasks/:taskId/progress - 查询任务进度
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* - GET /api/v1/dc/tool-b/tasks/:taskId/items - 获取验证网格数据
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* - POST /api/v1/dc/tool-b/items/:itemId/resolve - 裁决冲突
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*
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* 平台能力复用:
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* - ✅ logger: 日志记录
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* - ✅ prisma: 数据库操作
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* - ✅ storage: 文件操作
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* - ✅ jobQueue: 异步任务
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*/
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import { FastifyRequest, FastifyReply } from 'fastify';
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import { healthCheckService } from '../services/HealthCheckService.js';
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import { templateService } from '../services/TemplateService.js';
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import { dualModelExtractionService } from '../services/DualModelExtractionService.js';
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import { conflictDetectionService } from '../services/ConflictDetectionService.js';
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import { storage } from '../../../../common/storage/index.js';
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import { logger } from '../../../../common/logging/index.js';
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import { prisma } from '../../../../config/database.js';
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import * as xlsx from 'xlsx';
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export class ExtractionController {
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/**
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* 文件上传
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* POST /upload
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*/
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async uploadFile(request: FastifyRequest, reply: FastifyReply) {
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try {
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const data = await request.file();
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if (!data) {
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return reply.code(400).send({
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success: false,
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error: 'No file uploaded'
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});
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}
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const userId = (request as any).userId || 'default-user';
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const buffer = await data.toBuffer();
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const originalFilename = data.filename;
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const timestamp = Date.now();
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const fileKey = `dc/tool-b/${userId}/${timestamp}_${originalFilename}`;
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logger.info('[API] File upload request', {
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filename: originalFilename,
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size: buffer.length,
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userId
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});
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// 解析Excel文件获取列名和行数
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const workbook = xlsx.read(buffer, { type: 'buffer' });
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const sheetName = workbook.SheetNames[0];
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const worksheet = workbook.Sheets[sheetName];
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const jsonData = xlsx.utils.sheet_to_json<Record<string, any>>(worksheet);
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// 获取列名(从第一行数据的keys)
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const columns = jsonData.length > 0 ? Object.keys(jsonData[0]) : [];
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const totalRows = jsonData.length;
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logger.info('[API] Excel parsed', { columns, totalRows });
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// 上传到storage
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const url = await storage.upload(fileKey, buffer);
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logger.info('[API] File uploaded successfully', { fileKey, url });
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return reply.code(200).send({
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success: true,
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data: {
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fileKey,
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url,
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filename: originalFilename,
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size: buffer.length,
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totalRows,
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columns
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}
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});
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} catch (error) {
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logger.error('[API] File upload failed', { error });
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return reply.code(500).send({
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success: false,
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error: String(error)
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});
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}
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}
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/**
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* 健康检查
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* POST /health-check
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*/
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async healthCheck(request: FastifyRequest<{
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Body: {
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fileKey: string;
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columnName: string;
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}
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}>, reply: FastifyReply) {
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try {
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const { fileKey, columnName } = request.body;
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const userId = (request as any).userId || 'default-user'; // TODO: 从auth middleware获取
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logger.info('[API] Health check request', { fileKey, columnName, userId });
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// 参数验证
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if (!fileKey || !columnName) {
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logger.error('[API] Missing required parameters', { fileKey, columnName });
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return reply.code(400).send({
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success: false,
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error: 'Missing required parameters: fileKey or columnName'
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});
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}
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const result = await healthCheckService.check(fileKey, columnName, userId);
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logger.info('[API] Health check success', { status: result.status });
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return reply.code(200).send({
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success: true,
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data: result
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});
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} catch (error: any) {
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logger.error('[API] Health check failed', {
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error: error.message,
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stack: error.stack,
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fileKey: request.body?.fileKey,
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columnName: request.body?.columnName
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});
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return reply.code(500).send({
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success: false,
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error: error.message || String(error),
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details: process.env.NODE_ENV === 'development' ? error.stack : undefined
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});
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}
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}
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/**
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* 获取模板列表
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* GET /templates
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*/
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async getTemplates(request: FastifyRequest, reply: FastifyReply) {
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try {
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logger.info('[API] Get templates request');
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const templates = await templateService.getAllTemplates();
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return reply.code(200).send({
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success: true,
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data: { templates }
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});
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} catch (error) {
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logger.error('[API] Get templates failed', { error });
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return reply.code(500).send({
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success: false,
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error: String(error)
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});
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}
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}
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/**
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* 创建提取任务
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* POST /tasks
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*/
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async createTask(request: FastifyRequest<{
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Body: {
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projectName: string;
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sourceFileKey: string;
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textColumn: string;
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diseaseType: string;
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reportType: string;
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modelA?: string;
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modelB?: string;
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}
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}>, reply: FastifyReply) {
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try {
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logger.info('[API] ===== CREATE TASK START =====');
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const {
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projectName,
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sourceFileKey,
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textColumn,
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diseaseType,
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reportType,
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modelA = 'deepseek-v3',
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modelB = 'qwen-max'
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} = request.body;
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const userId = (request as any).userId || 'default-user';
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logger.info('[API] Create task request', {
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userId,
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projectName,
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sourceFileKey,
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textColumn,
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diseaseType,
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reportType
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});
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// 1. 获取模板
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logger.info('[API] Step 1: Getting template', { diseaseType, reportType });
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const template = await templateService.getTemplate(diseaseType, reportType);
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if (!template) {
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logger.error('[API] Template not found', { diseaseType, reportType });
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return reply.code(404).send({
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success: false,
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error: `Template not found: ${diseaseType}/${reportType}`
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});
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}
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logger.info('[API] Template found', { templateId: template.id });
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// 2. 读取Excel文件,创建items
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logger.info('[API] Step 2: Downloading Excel file', { sourceFileKey });
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const fileBuffer = await storage.download(sourceFileKey);
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if (!fileBuffer) {
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logger.error('[API] File not found in storage', { sourceFileKey });
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return reply.code(404).send({
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success: false,
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error: `File not found: ${sourceFileKey}`
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});
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}
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logger.info('[API] File downloaded', { size: fileBuffer.length });
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logger.info('[API] Step 3: Parsing Excel file');
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const workbook = xlsx.read(fileBuffer, { type: 'buffer' });
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const sheetName = workbook.SheetNames[0];
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const worksheet = workbook.Sheets[sheetName];
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const data = xlsx.utils.sheet_to_json<Record<string, any>>(worksheet);
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logger.info('[API] Excel parsed', { rowCount: data.length });
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if (!data[0].hasOwnProperty(textColumn)) {
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logger.error('[API] Column not found', {
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textColumn,
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availableColumns: Object.keys(data[0])
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});
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return reply.code(400).send({
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success: false,
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error: `Column '${textColumn}' not found in Excel`
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});
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}
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// 3. 创建任务
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logger.info('[API] Step 4: Creating task in database');
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const task = await prisma.dCExtractionTask.create({
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data: {
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userId,
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projectName,
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sourceFileKey,
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textColumn,
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diseaseType,
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reportType,
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targetFields: template.fields as any, // Prisma Json类型
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modelA,
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modelB,
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totalCount: data.length,
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status: 'pending'
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}
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});
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logger.info('[API] Task created in database', { taskId: task.id });
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// 4. 创建items
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logger.info('[API] Step 5: Creating extraction items', { count: data.length });
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const itemsData = data.map((row, index) => ({
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taskId: task.id,
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rowIndex: index + 1,
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originalText: String(row[textColumn] || '')
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}));
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await prisma.dCExtractionItem.createMany({
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data: itemsData
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});
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logger.info('[API] Items created', { count: itemsData.length });
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// 5. 启动异步任务
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// TODO: 使用jobQueue.add()
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// 暂时直接调用
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logger.info('[API] Starting batch extraction (async)', { taskId: task.id });
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dualModelExtractionService.batchExtract(task.id)
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.then(() => {
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logger.info('[API] Batch extraction completed successfully', { taskId: task.id });
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})
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.catch(err => {
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logger.error('[API] Batch extraction failed', {
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error: err.message,
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stack: err.stack,
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taskId: task.id
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});
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});
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logger.info('[API] Task created', { taskId: task.id, itemCount: data.length });
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return reply.code(201).send({
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success: true,
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data: {
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taskId: task.id,
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totalCount: data.length,
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status: 'pending'
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}
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});
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} catch (error) {
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logger.error('[API] Create task failed', { error });
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return reply.code(500).send({
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success: false,
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error: String(error)
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});
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}
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}
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/**
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* 查询任务进度
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* GET /tasks/:taskId/progress
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*/
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async getTaskProgress(request: FastifyRequest<{
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Params: { taskId: string }
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}>, reply: FastifyReply) {
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try {
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const { taskId } = request.params;
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logger.info('[API] Get task progress', { taskId });
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const task = await prisma.dCExtractionTask.findUnique({
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where: { id: taskId }
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});
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if (!task) {
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return reply.code(404).send({
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success: false,
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error: 'Task not found'
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});
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}
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return reply.code(200).send({
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success: true,
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data: {
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taskId: task.id,
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status: task.status,
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totalCount: task.totalCount,
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processedCount: task.processedCount,
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cleanCount: task.cleanCount,
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conflictCount: task.conflictCount,
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failedCount: task.failedCount,
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totalTokens: task.totalTokens,
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totalCost: task.totalCost,
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progress: task.totalCount > 0 ? Math.round((task.processedCount / task.totalCount) * 100) : 0
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}
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});
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} catch (error) {
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logger.error('[API] Get task progress failed', { error });
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return reply.code(500).send({
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success: false,
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error: String(error)
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});
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}
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}
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/**
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* 获取验证网格数据
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* GET /tasks/:taskId/items
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*/
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async getTaskItems(request: FastifyRequest<{
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Params: { taskId: string };
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Querystring: { page?: string; limit?: string; status?: string }
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}>, reply: FastifyReply) {
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try {
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const { taskId } = request.params;
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const page = parseInt(request.query.page || '1');
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const limit = parseInt(request.query.limit || '50');
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const statusFilter = request.query.status;
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logger.info('[API] Get task items', { taskId, page, limit, statusFilter });
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const where: any = { taskId };
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if (statusFilter) {
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where.status = statusFilter;
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}
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const [items, total] = await Promise.all([
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prisma.dCExtractionItem.findMany({
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where,
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skip: (page - 1) * limit,
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take: limit,
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orderBy: { rowIndex: 'asc' }
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}),
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prisma.dCExtractionItem.count({ where })
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]);
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return reply.code(200).send({
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success: true,
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data: {
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items: items.map(item => ({
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id: item.id,
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rowIndex: item.rowIndex,
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originalText: item.originalText,
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resultA: item.resultA,
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resultB: item.resultB,
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status: item.status,
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conflictFields: item.conflictFields,
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finalResult: item.finalResult
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})),
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pagination: {
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page,
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limit,
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total,
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totalPages: Math.ceil(total / limit)
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}
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}
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});
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} catch (error) {
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logger.error('[API] Get task items failed', { error });
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return reply.code(500).send({
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success: false,
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error: String(error)
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});
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}
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}
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/**
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* 裁决冲突
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* POST /items/:itemId/resolve
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*/
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async resolveConflict(request: FastifyRequest<{
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Params: { itemId: string };
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Body: {
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field: string;
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chosenValue: string;
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}
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}>, reply: FastifyReply) {
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try {
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const { itemId } = request.params;
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const { field, chosenValue } = request.body;
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logger.info('[API] Resolve conflict', { itemId, field });
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// 获取当前记录
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const item = await prisma.dCExtractionItem.findUnique({
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where: { id: itemId }
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});
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if (!item) {
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return reply.code(404).send({
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success: false,
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error: 'Item not found'
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});
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}
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// 更新finalResult
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const finalResult = { ...(item.finalResult as Record<string, string> || {}) };
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finalResult[field] = chosenValue;
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// 移除已解决的冲突字段
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const conflictFields = item.conflictFields.filter(f => f !== field);
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// 更新状态
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const newStatus = conflictFields.length === 0 ? 'resolved' : 'conflict';
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await prisma.dCExtractionItem.update({
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where: { id: itemId },
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data: {
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finalResult,
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conflictFields,
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status: newStatus,
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resolvedAt: conflictFields.length === 0 ? new Date() : null
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}
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});
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logger.info('[API] Conflict resolved', { itemId, field, newStatus });
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return reply.code(200).send({
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success: true,
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data: {
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itemId,
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status: newStatus,
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remainingConflicts: conflictFields.length
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}
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});
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} catch (error) {
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logger.error('[API] Resolve conflict failed', { error });
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return reply.code(500).send({
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success: false,
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error: String(error)
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});
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||
}
|
||
}
|
||
|
||
/**
|
||
* 导出结果
|
||
* GET /tasks/:taskId/export
|
||
*/
|
||
async exportResults(request: FastifyRequest<{
|
||
Params: { taskId: string };
|
||
}>, reply: FastifyReply) {
|
||
try {
|
||
const { taskId } = request.params;
|
||
|
||
logger.info('[API] Export results request', { taskId });
|
||
|
||
// 获取任务和所有items
|
||
const task = await prisma.dCExtractionTask.findUnique({
|
||
where: { id: taskId },
|
||
include: {
|
||
items: {
|
||
orderBy: { rowIndex: 'asc' }
|
||
}
|
||
}
|
||
});
|
||
|
||
if (!task) {
|
||
return reply.code(404).send({
|
||
success: false,
|
||
error: 'Task not found'
|
||
});
|
||
}
|
||
|
||
// 创建Excel工作簿
|
||
const workbook = xlsx.utils.book_new();
|
||
|
||
// 🔑 获取字段顺序(从targetFields)
|
||
const targetFields = task.targetFields as { name: string; desc: string }[];
|
||
const fieldNames = targetFields.map(f => f.name);
|
||
|
||
// 构建数据行,按模板字段顺序
|
||
const rows = task.items.map(item => {
|
||
// 优先使用finalResult,如果为空则使用resultA
|
||
const finalResult = item.finalResult as Record<string, string> | null;
|
||
const resultA = item.resultA as Record<string, string> | null;
|
||
const extractedData = finalResult || resultA || {};
|
||
|
||
// 🔑 按字段顺序构建行对象
|
||
const row: Record<string, any> = {
|
||
'行号': item.rowIndex,
|
||
'原文': item.originalText,
|
||
'状态': item.status === 'resolved' ? '已解决' : item.status === 'clean' ? '一致' : '待裁决'
|
||
};
|
||
|
||
// 按模板定义的顺序添加字段
|
||
fieldNames.forEach(fieldName => {
|
||
row[fieldName] = extractedData[fieldName] || '未提及';
|
||
});
|
||
|
||
return row;
|
||
});
|
||
|
||
// 创建工作表
|
||
const worksheet = xlsx.utils.json_to_sheet(rows);
|
||
xlsx.utils.book_append_sheet(workbook, worksheet, '提取结果');
|
||
|
||
// 生成Excel Buffer
|
||
const excelBuffer = xlsx.write(workbook, { type: 'buffer', bookType: 'xlsx' });
|
||
|
||
logger.info('[API] Export results success', { taskId, rowCount: rows.length });
|
||
|
||
// 返回文件
|
||
// 🔑 对文件名进行URL编码以支持中文
|
||
const filename = `${task.projectName}_结果.xlsx`;
|
||
const encodedFilename = encodeURIComponent(filename);
|
||
|
||
return reply
|
||
.code(200)
|
||
.header('Content-Type', 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet')
|
||
.header('Content-Disposition', `attachment; filename*=UTF-8''${encodedFilename}`)
|
||
.send(excelBuffer);
|
||
|
||
} catch (error) {
|
||
logger.error('[API] Export results failed', { error });
|
||
return reply.code(500).send({
|
||
success: false,
|
||
error: String(error)
|
||
});
|
||
}
|
||
}
|
||
}
|
||
|
||
// 导出单例
|
||
export const extractionController = new ExtractionController();
|
||
|
||
|
||
|
||
|
||
|
||
|