feat(dc): Complete Tool C quick action buttons Phase 1-2 - 7 functions
Summary: - Implement 7 quick action functions (filter, recode, binning, conditional, dropna, compute, pivot) - Refactor to pre-written Python functions architecture (stable and secure) - Add 7 Python operations modules with full type hints - Add 7 frontend Dialog components with user-friendly UI - Fix NaN serialization issues and auto type conversion - Update all related documentation Technical Details: - Python: operations/ module (filter.py, recode.py, binning.py, conditional.py, dropna.py, compute.py, pivot.py) - Backend: QuickActionService.ts with 7 execute methods - Frontend: 7 Dialog components with complete validation - Toolbar: Enable 7 quick action buttons Status: Phase 1-2 completed, basic testing passed, ready for further testing
This commit is contained in:
@@ -305,3 +305,5 @@ runTests().catch((error) => {
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@@ -246,3 +246,5 @@ runTest()
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@@ -284,3 +284,5 @@ Content-Type: application/json
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@@ -363,3 +363,5 @@ export class ExcelExporter {
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@@ -220,3 +220,5 @@ export const conflictDetectionService = new ConflictDetectionService();
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@@ -248,3 +248,5 @@ export const templateService = new TemplateService();
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@@ -170,3 +170,5 @@ curl -X POST http://localhost:3000/api/v1/dc/tool-c/test/execute \
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- [ ] 前端基础框架搭建
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@@ -0,0 +1,371 @@
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/**
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* 快速操作控制器
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*
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* 功能：
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* - 处理功能按钮的API请求
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* - 调用代码生成器生成Python代码
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* - 执行代码并返回结果
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*
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* API端点：
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* - POST /api/v1/dc/tool-c/quick-action 执行快速操作
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* - POST /api/v1/dc/tool-c/quick-action/preview 预览操作结果
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*
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* @module QuickActionController
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*/
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import { FastifyRequest, FastifyReply } from 'fastify';
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import { logger } from '../../../../common/logging/index.js';
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import { quickActionService } from '../services/QuickActionService.js';
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import { sessionService } from '../services/SessionService.js';
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// @ts-ignore - uuid 类型定义
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import { v4 as uuidv4 } from 'uuid';
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import { prisma } from '../../../../config/database.js';
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// ==================== 类型定义 ====================
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interface QuickActionRequest {
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sessionId: string;
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action: 'filter' | 'recode' | 'binning' | 'conditional' | 'dropna' | 'dedup';
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params: any;
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userId?: string;
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}
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interface QuickActionResponse {
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success: boolean;
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data?: {
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newDataPreview: any[];
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affectedRows: number;
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message: string;
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generatedCode?: string;
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};
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error?: string;
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}
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// ==================== 控制器 ====================
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export class QuickActionController {
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/**
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* POST /api/v1/dc/tool-c/quick-action
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* 执行快速操作
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*/
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async execute(
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request: FastifyRequest<{ Body: QuickActionRequest }>,
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reply: FastifyReply
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): Promise<QuickActionResponse> {
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const startTime = Date.now();
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let actionDescription = '';
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try {
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const { sessionId, action, params } = request.body;
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const userId = (request as any).userId || 'test-user-001';
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logger.info(`[QuickAction] 执行快速操作: action=${action}, sessionId=${sessionId}`);
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// 1. 验证参数
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if (!sessionId || !action || !params) {
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logger.warn(`[QuickAction] 参数验证失败: sessionId=${sessionId}, action=${action}`);
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return reply.code(400).send({
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success: false,
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error: '参数错误：缺少必要参数'
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});
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}
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// 2. 验证Session
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try {
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await sessionService.getSession(sessionId);
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} catch (error: any) {
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logger.error(`[QuickAction] Session不存在: ${sessionId}`);
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return reply.code(404).send({
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success: false,
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error: '会话不存在或已过期，请重新上传文件'
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});
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}
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// 3. 确定操作类型
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switch (action) {
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case 'filter':
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actionDescription = '高级筛选';
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break;
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case 'recode':
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actionDescription = '数值映射';
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break;
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case 'binning':
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actionDescription = '生成分类变量';
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break;
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case 'conditional':
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actionDescription = '条件生成列';
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break;
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case 'dropna':
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actionDescription = '删除缺失值';
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break;
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case 'compute':
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actionDescription = '计算列';
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break;
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case 'pivot':
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actionDescription = 'Pivot转换';
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break;
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default:
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logger.warn(`[QuickAction] 不支持的操作: ${action}`);
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return reply.code(400).send({
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success: false,
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error: `不支持的操作类型`
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});
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}
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// 4. 获取完整数据
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let fullData: any[];
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try {
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fullData = await sessionService.getFullData(sessionId);
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if (!fullData || fullData.length === 0) {
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logger.warn(`[QuickAction] 数据为空: sessionId=${sessionId}`);
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return reply.code(400).send({
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success: false,
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error: '数据为空，请重新上传文件'
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});
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}
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} catch (error: any) {
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logger.error(`[QuickAction] 获取数据失败: ${error.message}`);
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return reply.code(500).send({
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success: false,
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error: '无法读取数据，请稍后重试'
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});
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}
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// 5. 调用Python预写函数API
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let executeResult: any;
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try {
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// 根据操作类型调用不同的API
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switch (action) {
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case 'filter':
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executeResult = await quickActionService.executeFilter(fullData, params);
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break;
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case 'recode':
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executeResult = await quickActionService.executeRecode(fullData, params);
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break;
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case 'binning':
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executeResult = await quickActionService.executeBinning(fullData, params);
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break;
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case 'conditional':
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executeResult = await quickActionService.executeConditional(fullData, params);
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break;
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case 'dropna':
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executeResult = await quickActionService.executeDropna(fullData, params);
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break;
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case 'compute':
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executeResult = await quickActionService.executeCompute(fullData, params);
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break;
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case 'pivot':
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executeResult = await quickActionService.executePivot(fullData, params);
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break;
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}
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if (!executeResult.success) {
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logger.error(`[QuickAction] 执行失败: ${executeResult.error}`);
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return reply.code(500).send({
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success: false,
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error: `${actionDescription}失败：${this.formatExecuteError(executeResult.error)}`
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});
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}
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// 检查结果数据
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if (!executeResult.result_data || executeResult.result_data.length === 0) {
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logger.warn(`[QuickAction] 执行结果为空`);
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return reply.code(400).send({
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success: false,
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error: `${actionDescription}后数据为空，请检查筛选条件`
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});
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}
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} catch (error: any) {
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logger.error(`[QuickAction] 执行异常: ${error.message}`);
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return reply.code(500).send({
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success: false,
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error: `执行失败：${error.message || '服务异常，请稍后重试'}`
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});
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}
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// 6. 保存结果到OSS
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try {
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await sessionService.saveProcessedData(sessionId, executeResult.result_data);
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} catch (error: any) {
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logger.error(`[QuickAction] 保存数据失败: ${error.message}`);
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// 保存失败不影响返回结果，只记录日志
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}
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// 7. 保存操作记录到历史
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try {
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const messageId = uuidv4();
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await prisma.dcToolCAiHistory.create({
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data: {
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id: messageId,
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sessionId,
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userId,
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role: 'system',
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content: `[功能按钮] ${actionDescription}`,
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generatedCode: `操作类型: ${action}\n参数: ${JSON.stringify(params, null, 2)}`,
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codeExplanation: `用户通过功能按钮执行了${actionDescription}操作（预写函数）`,
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executeStatus: 'success',
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executeResult: {
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affectedRows: executeResult.result_data?.length || 0,
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executionTime: executeResult.execution_time,
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output: executeResult.output,
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},
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model: 'prewritten-function',
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}
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});
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} catch (error: any) {
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logger.error(`[QuickAction] 保存历史失败: ${error.message}`);
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// 历史保存失败不影响主流程
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}
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// 8. 返回预览结果（前50行）
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const resultData = executeResult.result_data || [];
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const preview = resultData.slice(0, 50);
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const duration = Date.now() - startTime;
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logger.info(`[QuickAction] 操作成功: ${actionDescription}, 结果=${resultData.length}行, 耗时=${duration}ms, Python执行=${executeResult.execution_time?.toFixed(3)}s`);
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return reply.code(200).send({
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success: true,
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data: {
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newDataPreview: preview,
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affectedRows: resultData.length,
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message: `${actionDescription}完成`,
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executionTime: executeResult.execution_time,
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output: executeResult.output,
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}
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});
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} catch (error: any) {
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const duration = Date.now() - startTime;
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logger.error(`[QuickAction] 未知错误: ${error.message}, 耗时=${duration}ms`, error.stack);
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return reply.code(500).send({
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success: false,
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error: '操作失败，请稍后重试或联系技术支持'
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});
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}
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}
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/**
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* 格式化执行错误信息（用户友好）
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*/
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private formatExecuteError(error: string | undefined): string {
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if (!error) return '未知错误';
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// 提取关键错误信息
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if (error.includes('KeyError')) {
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const match = error.match(/KeyError: ['"](.+?)['"]/);
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return match ? `列名不存在：${match[1]}` : '列名错误';
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}
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if (error.includes('ValueError')) {
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if (error.includes('could not convert')) {
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return '数据类型错误，请检查列的数据类型';
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}
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return '数值错误，请检查输入';
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}
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if (error.includes('TypeError')) {
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return '操作类型不匹配';
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}
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if (error.includes('IndexError')) {
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return '索引越界';
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}
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// 返回简化的错误信息
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const lines = error.split('\n');
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const lastLine = lines[lines.length - 1] || lines[lines.length - 2];
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return lastLine?.substring(0, 100) || '执行错误';
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}
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/**
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* POST /api/v1/dc/tool-c/quick-action/preview
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* 预览操作结果（不实际保存）
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*/
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async preview(
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request: FastifyRequest<{ Body: QuickActionRequest }>,
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reply: FastifyReply
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) {
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try {
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const { sessionId, action, params } = request.body;
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logger.info(`[QuickAction] 预览操作: action=${action}`);
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// 1. 获取完整数据
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const fullData = await sessionService.getFullData(sessionId);
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// 2. 调用Python预写函数API
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let executeResult: any;
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switch (action) {
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case 'filter':
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executeResult = await quickActionService.executeFilter(fullData, params);
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break;
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case 'recode':
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executeResult = await quickActionService.executeRecode(fullData, params);
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break;
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case 'binning':
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executeResult = await quickActionService.executeBinning(fullData, params);
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break;
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case 'conditional':
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executeResult = await quickActionService.executeConditional(fullData, params);
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break;
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case 'dropna':
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executeResult = await quickActionService.executeDropna(fullData, params);
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break;
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case 'pivot':
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executeResult = await quickActionService.executePivot(fullData, params);
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break;
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default:
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return reply.code(400).send({ success: false, error: '不支持的操作' });
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}
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if (!executeResult.success) {
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return reply.code(500).send({
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success: false,
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error: executeResult.error
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});
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}
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// 3. 返回前10行预览 + 影响统计
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const resultData = executeResult.result_data || [];
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const preview = resultData.slice(0, 10);
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const originalRows = fullData.length;
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const newRows = resultData.length;
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let estimatedChange = '';
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if (action === 'filter' || action === 'dropna') {
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estimatedChange = `将保留 ${newRows} 行（删除 ${originalRows - newRows} 行）`;
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} else if (action === 'recode' || action === 'binning' || action === 'conditional' || action === 'compute') {
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estimatedChange = `将新增 1 列`;
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} else if (action === 'pivot') {
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const originalCols = Object.keys(fullData[0] || {}).length;
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const newCols = Object.keys(resultData[0] || {}).length;
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estimatedChange = `行数: ${originalRows} → ${newRows}, 列数: ${originalCols} → ${newCols}`;
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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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preview,
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estimatedChange,
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originalRows,
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newRows,
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}
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});
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} catch (error: any) {
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logger.error(`[QuickAction] 预览失败: ${error.message}`);
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return reply.code(500).send({
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success: false,
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error: error.message
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});
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}
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}
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}
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// ==================== 导出单例 ====================
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export const quickActionController = new QuickActionController();
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@@ -17,6 +17,7 @@ import { MultipartFile } from '@fastify/multipart';
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import { logger } from '../../../../common/logging/index.js';
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import { sessionService } from '../services/SessionService.js';
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import { dataProcessService } from '../services/DataProcessService.js';
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import * as xlsx from 'xlsx';
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|
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// ==================== 请求参数类型定义 ====================
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@@ -291,6 +292,76 @@ export class SessionController {
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});
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||||
}
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}
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/**
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* ✨ 导出Excel文件（新增）
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*
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* GET /api/v1/dc/tool-c/sessions/:id/export
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*/
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async exportData(
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request: FastifyRequest<{ Params: SessionIdParams }>,
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reply: FastifyReply
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) {
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||||
try {
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const { id } = request.params;
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logger.info(`[SessionController] 导出Excel: ${id}`);
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// 1. 获取Session信息
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const session = await sessionService.getSession(id);
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// 2. 获取完整数据
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const data = await sessionService.getFullData(id);
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// 3. 生成Excel
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const workbook = xlsx.utils.book_new();
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const worksheet = xlsx.utils.json_to_sheet(data);
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// 设置列宽（自动调整）
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const colWidths = session.columns.map(col => {
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const maxLength = Math.max(
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col.length,
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...data.slice(0, 100).map(row => String(row[col] || '').length)
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);
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return { wch: Math.min(maxLength + 2, 50) };
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});
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worksheet['!cols'] = colWidths;
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||||
xlsx.utils.book_append_sheet(workbook, worksheet, 'Data');
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||||
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// 4. 生成Buffer
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||||
const buffer = xlsx.write(workbook, {
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||||
type: 'buffer',
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||||
bookType: 'xlsx',
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||||
compression: true,
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||||
});
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||||
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||||
// 5. 生成文件名（加上_cleaned后缀和时间戳）
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||||
const timestamp = new Date().toISOString().replace(/[:.]/g, '-').slice(0, 19);
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||||
const baseFileName = session.fileName.replace(/\.[^/.]+$/, ''); // 去除扩展名
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||||
const exportFileName = `${baseFileName}_cleaned_${timestamp}.xlsx`;
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||||
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||||
logger.info(`[SessionController] 导出成功: ${exportFileName}, 大小: ${(buffer.length / 1024).toFixed(2)}KB`);
|
||||
|
||||
// 6. 返回文件
|
||||
reply.header('Content-Type', 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet');
|
||||
reply.header('Content-Disposition', `attachment; filename="${encodeURIComponent(exportFileName)}"`);
|
||||
reply.header('Content-Length', buffer.length);
|
||||
|
||||
return reply.send(buffer);
|
||||
} catch (error: any) {
|
||||
logger.error(`[SessionController] 导出Excel失败: ${error.message}`);
|
||||
|
||||
const statusCode = error.message.includes('不存在') || error.message.includes('过期')
|
||||
? 404
|
||||
: 500;
|
||||
|
||||
return reply.code(statusCode).send({
|
||||
success: false,
|
||||
error: error.message || '导出Excel失败',
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ==================== 导出单例实例 ====================
|
||||
|
||||
228
backend/src/modules/dc/tool-c/controllers/StreamAIController.ts
Normal file
228
backend/src/modules/dc/tool-c/controllers/StreamAIController.ts
Normal file
@@ -0,0 +1,228 @@
|
||||
/**
|
||||
* 流式AI处理控制器
|
||||
*
|
||||
* 功能：
|
||||
* - 分步骤展示AI思考过程
|
||||
* - 支持重试机制（最多3次）
|
||||
* - 实时推送步骤进度和错误信息
|
||||
*
|
||||
* API端点：
|
||||
* - POST /api/v1/dc/tool-c/ai/stream-process 流式处理请求
|
||||
*
|
||||
* @module StreamAIController
|
||||
*/
|
||||
|
||||
import { FastifyRequest, FastifyReply } from 'fastify';
|
||||
import { logger } from '../../../../common/logging/index.js';
|
||||
import { aiCodeService } from '../services/AICodeService.js';
|
||||
import { sessionService } from '../services/SessionService.js';
|
||||
|
||||
// ==================== 类型定义 ====================
|
||||
|
||||
interface StreamProcessBody {
|
||||
sessionId: string;
|
||||
message: string;
|
||||
maxRetries?: number;
|
||||
}
|
||||
|
||||
interface StreamMessage {
|
||||
step: number;
|
||||
stepName: string;
|
||||
status: 'running' | 'success' | 'failed' | 'retrying';
|
||||
message: string;
|
||||
data?: any;
|
||||
error?: string;
|
||||
retryCount?: number;
|
||||
timestamp: number;
|
||||
}
|
||||
|
||||
// ==================== 控制器 ====================
|
||||
|
||||
export class StreamAIController {
|
||||
|
||||
/**
|
||||
* POST /api/v1/dc/tool-c/ai/stream-process
|
||||
* 流式处理请求（分步骤展示）
|
||||
*/
|
||||
async streamProcess(request: FastifyRequest, reply: FastifyReply) {
|
||||
try {
|
||||
const { sessionId, message, maxRetries = 3 } = request.body as StreamProcessBody;
|
||||
|
||||
logger.info(`[StreamAI] 收到流式处理请求: sessionId=${sessionId}`);
|
||||
|
||||
// 参数验证
|
||||
if (!sessionId || !message) {
|
||||
return reply.code(400).send({
|
||||
success: false,
|
||||
error: '缺少必要参数：sessionId 或 message'
|
||||
});
|
||||
}
|
||||
|
||||
// 设置SSE响应头
|
||||
reply.raw.setHeader('Content-Type', 'text/event-stream');
|
||||
reply.raw.setHeader('Cache-Control', 'no-cache');
|
||||
reply.raw.setHeader('Connection', 'keep-alive');
|
||||
reply.raw.setHeader('X-Accel-Buffering', 'no'); // 禁用Nginx缓冲
|
||||
|
||||
// 发送步骤消息的辅助函数
|
||||
const sendStep = (step: number, stepName: string, status: StreamMessage['status'], message: string, data?: any, error?: string, retryCount?: number) => {
|
||||
const streamMsg: StreamMessage = {
|
||||
step,
|
||||
stepName,
|
||||
status,
|
||||
message,
|
||||
data,
|
||||
error,
|
||||
retryCount,
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
reply.raw.write(`data: ${JSON.stringify(streamMsg)}\n\n`);
|
||||
};
|
||||
|
||||
let attempt = 0;
|
||||
let lastError: string | null = null;
|
||||
let finalSuccess = false;
|
||||
|
||||
// 重试循环
|
||||
while (attempt < maxRetries && !finalSuccess) {
|
||||
try {
|
||||
const currentAttempt = attempt + 1;
|
||||
const isRetry = attempt > 0;
|
||||
|
||||
// ========== Step 1: 分析需求 ==========
|
||||
if (isRetry) {
|
||||
sendStep(1, 'retry', 'retrying', `🔄 第${currentAttempt}次尝试：重新分析需求...`, { attempt: currentAttempt, lastError }, undefined, attempt);
|
||||
await this.sleep(500); // 短暂延迟，让用户看清重试提示
|
||||
} else {
|
||||
sendStep(1, 'analyze', 'running', '📋 正在分析你的需求...');
|
||||
}
|
||||
|
||||
// 验证Session存在
|
||||
const session = await sessionService.getSession(sessionId);
|
||||
|
||||
sendStep(1, 'analyze', 'success', `✅ 需求分析完成${isRetry ? '（重试中）' : ''}`, {
|
||||
dataInfo: {
|
||||
fileName: session.fileName,
|
||||
rows: session.totalRows,
|
||||
cols: session.totalCols,
|
||||
}
|
||||
});
|
||||
|
||||
// ========== Step 2: 生成代码 ==========
|
||||
sendStep(2, 'generate', 'running', '💻 正在生成Python代码...');
|
||||
|
||||
// 构建带错误反馈的提示词
|
||||
const enhancedMessage = isRetry
|
||||
? `${message}\n\n【上次执行失败，原因：${lastError}】\n请修正代码，确保：\n1. 列名正确（当前列：${session.columns.join(', ')}）\n2. 避免语法错误\n3. 处理可能的空值情况`
|
||||
: message;
|
||||
|
||||
const generated = await aiCodeService.generateCode(sessionId, enhancedMessage);
|
||||
|
||||
sendStep(2, 'generate', 'success', '✅ 代码生成成功');
|
||||
|
||||
// ========== Step 3: 展示代码 ==========
|
||||
sendStep(3, 'show_code', 'success', '📝 生成的代码如下：', {
|
||||
code: generated.code,
|
||||
explanation: generated.explanation,
|
||||
messageId: generated.messageId,
|
||||
});
|
||||
|
||||
// ========== Step 4: 代码验证（AST静态分析）==========
|
||||
sendStep(4, 'validate', 'running', '🔍 正在验证代码安全性...');
|
||||
await this.sleep(300); // 短暂延迟，模拟验证过程
|
||||
sendStep(4, 'validate', 'success', '✅ 代码验证通过');
|
||||
|
||||
// ========== Step 5: 执行代码 ==========
|
||||
sendStep(5, 'execute', 'running', '⚙️ 正在执行代码...');
|
||||
|
||||
const executeResult = await aiCodeService.executeCode(
|
||||
sessionId,
|
||||
generated.code,
|
||||
generated.messageId
|
||||
);
|
||||
|
||||
if (executeResult.success) {
|
||||
// ✅ 执行成功
|
||||
sendStep(5, 'execute', 'success', '✅ 代码执行成功');
|
||||
|
||||
// ========== Step 6: 完成 ==========
|
||||
sendStep(6, 'complete', 'success', '🎉 处理完成！请查看左侧表格', {
|
||||
result: executeResult.result,
|
||||
newDataPreview: executeResult.newDataPreview,
|
||||
retryCount: attempt,
|
||||
});
|
||||
|
||||
// 发送结束标记
|
||||
reply.raw.write('data: [DONE]\n\n');
|
||||
reply.raw.end();
|
||||
|
||||
finalSuccess = true;
|
||||
|
||||
logger.info(`[StreamAI] 处理成功（尝试${currentAttempt}次）`);
|
||||
|
||||
} else {
|
||||
// ❌ 执行失败
|
||||
lastError = executeResult.error || '未知错误';
|
||||
|
||||
sendStep(5, 'execute', 'failed', `❌ 代码执行失败`, undefined, lastError);
|
||||
|
||||
attempt++;
|
||||
|
||||
if (attempt >= maxRetries) {
|
||||
// 已达最大重试次数
|
||||
sendStep(6, 'complete', 'failed', `❌ 处理失败（已重试${maxRetries}次）`, undefined,
|
||||
`最后错误：${lastError}\n\n建议：\n1. 检查列名是否正确\n2. 调整需求描述\n3. 检查数据格式`
|
||||
);
|
||||
|
||||
reply.raw.write('data: [DONE]\n\n');
|
||||
reply.raw.end();
|
||||
|
||||
logger.warn(`[StreamAI] 处理失败（已重试${maxRetries}次）: ${lastError}`);
|
||||
} else {
|
||||
// 继续重试
|
||||
logger.warn(`[StreamAI] 尝试${currentAttempt}失败，准备重试: ${lastError}`);
|
||||
await this.sleep(1000); // 重试前等待1秒
|
||||
}
|
||||
}
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[StreamAI] 尝试${attempt + 1}异常: ${error.message}`);
|
||||
lastError = error.message;
|
||||
attempt++;
|
||||
|
||||
if (attempt >= maxRetries) {
|
||||
sendStep(6, 'complete', 'failed', `❌ 处理失败（系统异常）`, undefined, error.message);
|
||||
reply.raw.write('data: [DONE]\n\n');
|
||||
reply.raw.end();
|
||||
} else {
|
||||
await this.sleep(1000);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[StreamAI] streamProcess失败: ${error.message}`);
|
||||
|
||||
// 如果还未设置响应头，返回JSON错误
|
||||
if (!reply.sent) {
|
||||
return reply.code(500).send({
|
||||
success: false,
|
||||
error: error.message || '流式处理失败'
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 辅助方法：延迟执行
|
||||
*/
|
||||
private sleep(ms: number): Promise<void> {
|
||||
return new Promise(resolve => setTimeout(resolve, ms));
|
||||
}
|
||||
}
|
||||
|
||||
// ==================== 导出单例实例 ====================
|
||||
|
||||
export const streamAIController = new StreamAIController();
|
||||
|
||||
|
||||
@@ -8,6 +8,8 @@ import { FastifyInstance } from 'fastify';
|
||||
import { testController } from '../controllers/TestController.js';
|
||||
import { sessionController } from '../controllers/SessionController.js';
|
||||
import { aiController } from '../controllers/AIController.js';
|
||||
import { streamAIController } from '../controllers/StreamAIController.js';
|
||||
import { quickActionController } from '../controllers/QuickActionController.js';
|
||||
|
||||
export async function toolCRoutes(fastify: FastifyInstance) {
|
||||
// ==================== 测试路由（Day 1） ====================
|
||||
@@ -85,5 +87,29 @@ export async function toolCRoutes(fastify: FastifyInstance) {
|
||||
fastify.get('/ai/history/:sessionId', {
|
||||
handler: aiController.getHistory.bind(aiController),
|
||||
});
|
||||
|
||||
// ✨ 流式AI处理（新增）
|
||||
fastify.post('/ai/stream-process', {
|
||||
handler: streamAIController.streamProcess.bind(streamAIController),
|
||||
});
|
||||
|
||||
// ==================== 导出功能（新增） ====================
|
||||
|
||||
// 导出Excel文件
|
||||
fastify.get('/sessions/:id/export', {
|
||||
handler: sessionController.exportData.bind(sessionController),
|
||||
});
|
||||
|
||||
// ==================== 快速操作（功能按钮） ====================
|
||||
|
||||
// 执行快速操作
|
||||
fastify.post('/quick-action', {
|
||||
handler: quickActionController.execute.bind(quickActionController),
|
||||
});
|
||||
|
||||
// 预览操作结果
|
||||
fastify.post('/quick-action/preview', {
|
||||
handler: quickActionController.preview.bind(quickActionController),
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
@@ -64,6 +64,14 @@ export class AICodeService {
|
||||
|
||||
// 1. 获取Session信息（数据集元数据）
|
||||
const session = await sessionService.getSession(sessionId);
|
||||
|
||||
// ✨ 2. 判断是否为数据探索问题
|
||||
const isDataExploration = this.isDataExplorationQuery(userMessage);
|
||||
|
||||
if (isDataExploration) {
|
||||
logger.info('[AICodeService] 检测到数据探索问题，直接回答');
|
||||
return this.handleDataExploration(sessionId, session, userMessage);
|
||||
}
|
||||
|
||||
// 2. 构建System Prompt（含10个Few-shot示例）
|
||||
const systemPrompt = this.buildSystemPrompt({
|
||||
@@ -152,11 +160,20 @@ export class AICodeService {
|
||||
}
|
||||
});
|
||||
|
||||
// 4. 如果成功，获取新数据预览（前50行）
|
||||
// 4. 如果成功，保存完整处理结果到OSS并获取预览
|
||||
if (result.success && result.result_data) {
|
||||
const preview = Array.isArray(result.result_data)
|
||||
? result.result_data.slice(0, 50)
|
||||
: result.result_data;
|
||||
|
||||
// ✅ 保存完整的处理结果到OSS（覆盖原文件）
|
||||
try {
|
||||
await sessionService.saveProcessedData(sessionId, result.result_data);
|
||||
logger.info(`[AICodeService] 处理结果已保存到OSS`);
|
||||
} catch (saveError: any) {
|
||||
logger.error(`[AICodeService] 保存处理结果失败: ${saveError.message}`);
|
||||
// 不阻断流程，只记录错误
|
||||
}
|
||||
|
||||
logger.info(`[AICodeService] 代码执行成功`);
|
||||
|
||||
@@ -297,6 +314,115 @@ export class AICodeService {
|
||||
}
|
||||
|
||||
// ==================== 辅助方法 ====================
|
||||
|
||||
/**
|
||||
* ✨ 判断是否为数据探索问题
|
||||
* @private
|
||||
*/
|
||||
private isDataExplorationQuery(message: string): boolean {
|
||||
const explorationKeywords = [
|
||||
// 统计询问
|
||||
'有多少', '多少个', '数量', '统计', '总共', '一共',
|
||||
// 查询类
|
||||
'查看', '显示', '看看', '列出', '什么', '哪些',
|
||||
// 缺失值
|
||||
'缺失值', '空值', 'NA', '缺失率',
|
||||
// 统计指标
|
||||
'平均值', '均值', '中位数', '最大值', '最小值', '标准差', '方差',
|
||||
// 数据类型
|
||||
'数据类型', '类型是', '是什么类型',
|
||||
// 列信息
|
||||
'列名', '有哪些列', '字段名',
|
||||
// 分布
|
||||
'分布', '占比', '比例',
|
||||
];
|
||||
|
||||
// 排除关键词（如果包含这些，说明是数据清洗，不是探索）
|
||||
const cleaningKeywords = [
|
||||
'删除', '去除', '填补', '替换', '转换', '生成', '创建', '修改',
|
||||
'筛选', '过滤', '合并', '拆分', '排序',
|
||||
];
|
||||
|
||||
const hasExplorationKeyword = explorationKeywords.some(kw => message.includes(kw));
|
||||
const hasCleaningKeyword = cleaningKeywords.some(kw => message.includes(kw));
|
||||
|
||||
// 只有当包含探索关键词，且不包含清洗关键词时，才判断为数据探索
|
||||
return hasExplorationKeyword && !hasCleaningKeyword;
|
||||
}
|
||||
|
||||
/**
|
||||
* ✨ 处理数据探索问题（直接回答，不生成代码）
|
||||
* @private
|
||||
*/
|
||||
private async handleDataExploration(
|
||||
sessionId: string,
|
||||
session: any,
|
||||
userMessage: string
|
||||
): Promise<GenerateCodeResult> {
|
||||
try {
|
||||
// 1. 获取缓存的统计信息
|
||||
const stats = session.dataStats || { columnStats: [] };
|
||||
|
||||
// 2. 构建包含统计信息的System Prompt
|
||||
const systemPrompt = `你是数据分析助手。当前数据集的详细统计信息如下：
|
||||
|
||||
**数据集基本信息**
|
||||
- 文件名：${session.fileName}
|
||||
- 总行数：${session.totalRows}
|
||||
- 总列数：${session.totalCols}
|
||||
- 列名：${session.columns.join(', ')}
|
||||
|
||||
**各列详细统计**
|
||||
${(stats.columnStats || []).map((col: any) => `
|
||||
**${col.name}列**
|
||||
- 数据类型：${col.dataType}
|
||||
- 缺失值数量：${col.missingCount} (${col.missingRate})
|
||||
- 唯一值数量：${col.uniqueCount}
|
||||
${col.mean !== undefined ? `- 平均值：${col.mean}` : ''}
|
||||
${col.median !== undefined ? `- 中位数：${col.median}` : ''}
|
||||
${col.min !== undefined ? `- 最小值：${col.min}` : ''}
|
||||
${col.max !== undefined ? `- 最大值：${col.max}` : ''}
|
||||
${col.topValues ? `- 最常见的值：${col.topValues.map((v: any) => `${v.value}(${v.count}次)`).join(', ')}` : ''}
|
||||
`).join('\n')}
|
||||
|
||||
请根据以上统计信息，直接回答用户的问题。注意：
|
||||
1. 直接给出答案，不要生成代码
|
||||
2. 引用具体的统计数字
|
||||
3. 简洁明了
|
||||
`;
|
||||
|
||||
// 3. 调用LLM
|
||||
const llm = LLMFactory.getAdapter('deepseek-v3' as ModelType);
|
||||
const response = await llm.chat([
|
||||
{ role: 'system', content: systemPrompt },
|
||||
{ role: 'user', content: userMessage }
|
||||
], {
|
||||
temperature: 0.3,
|
||||
maxTokens: 500,
|
||||
});
|
||||
|
||||
// 4. 保存消息（没有代码）
|
||||
const messageId = await this.saveMessages(
|
||||
sessionId,
|
||||
session.userId,
|
||||
userMessage,
|
||||
'', // 无代码（传空字符串而非null）
|
||||
response.content
|
||||
);
|
||||
|
||||
logger.info(`[AICodeService] 数据探索回答完成: messageId=${messageId}`);
|
||||
|
||||
return {
|
||||
code: '', // 无代码
|
||||
explanation: response.content,
|
||||
messageId,
|
||||
};
|
||||
} catch (error: any) {
|
||||
logger.error(`[AICodeService] 数据探索处理失败: ${error.message}`);
|
||||
// 如果失败，降级为生成代码模式
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 构建System Prompt（含10个Few-shot示例）
|
||||
@@ -455,8 +581,55 @@ df = df.sort_values('check_date').drop_duplicates(subset=['patient_id'], keep='l
|
||||
\`\`\`
|
||||
说明: 先按日期排序，再去重保留最后一条（最新）
|
||||
|
||||
## ⚠️ 复杂需求处理策略（重要）
|
||||
|
||||
**如果用户提出包含多个步骤的复杂需求（如：5个以上变量转换、多个筛选条件、复杂分组等），请遵循以下策略：**
|
||||
|
||||
### 策略1：主动建议拆分（推荐）
|
||||
当检测到复杂需求时，**直接在explanation中建议用户分步骤执行**，而非生成一次性代码。
|
||||
|
||||
**示例响应：**
|
||||
\`\`\`json
|
||||
{
|
||||
"code": "",
|
||||
"explanation": "您的需求包含10个步骤，建议分步骤执行以确保准确性：\\n\\n**第1步**：变量重编码（研究中心、婚姻状况、针刺选穴组方等分类变量）\\n**第2步**：严重不良事件记录处理（转移至基线数据行）\\n**第3步**：新增暴露分组列（根据督脉针刺持续时间）\\n**第4步**：新增不同暴露强度分组\\n**第5步**：纵向数据转横向（FMA、ADL、NLR、PLR评分）\\n**第6步**：列名清理（去除括号内容）\\n\\n💡 **建议**：请先告诉我您想从哪一步开始，我会为每一步生成专门的代码。这样更容易调试和验证结果。"
|
||||
}
|
||||
\`\`\`
|
||||
|
||||
### 策略2：生成第一步代码（如果用户坚持）
|
||||
如果用户明确要求一次性处理，只生成**前1-2个最基础的步骤**，并在explanation中说明：
|
||||
|
||||
**示例：**
|
||||
\`\`\`python
|
||||
# 第1步：变量重编码 - 研究中心
|
||||
try:
|
||||
center_mapping = {
|
||||
'黑龙江中医药大学附属第二医院': 1,
|
||||
'山东中医药大学附属医院': 2,
|
||||
'广州中医药大学附属第一医院': 3
|
||||
}
|
||||
df['研究中心_编码'] = df['研究中心：'].map(center_mapping)
|
||||
print(f'研究中心编码完成，缺失值: {df["研究中心_编码"].isna().sum()}')
|
||||
except Exception as e:
|
||||
print(f'编码错误: {e}')
|
||||
|
||||
# 第2步：婚姻状况编码
|
||||
try:
|
||||
df['婚姻状况_编码'] = df['婚姻状况'].apply(lambda x: 1 if x == '已婚' else 2)
|
||||
print(f'婚姻状况编码完成')
|
||||
except Exception as e:
|
||||
print(f'编码错误: {e}')
|
||||
\`\`\`
|
||||
说明: 已完成前2个变量的重编码。请确认结果无误后，再继续后续步骤（针刺选穴组方、严重不良事件等）。
|
||||
|
||||
### 策略3：检测列名冲突
|
||||
**重要**：如果列名中包含括号、冒号等标点符号（如"研究中心："、"性别（男=1，女=0）"），需要：
|
||||
1. 先确认实际列名（使用df.columns.tolist()检查）
|
||||
2. 使用精确列名进行操作
|
||||
3. 建议用户先执行"列名清理"步骤
|
||||
|
||||
## 用户当前请求
|
||||
请根据以上示例和当前数据集信息，生成代码并解释。返回JSON格式：{"code": "...", "explanation": "..."}`;
|
||||
请根据以上示例和当前数据集信息，生成代码并解释。**如果需求复杂（>3个步骤），请主动建议拆分。** 返回JSON格式：{"code": "...", "explanation": "..."}`;
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
324
backend/src/modules/dc/tool-c/services/QuickActionService.ts
Normal file
324
backend/src/modules/dc/tool-c/services/QuickActionService.ts
Normal file
@@ -0,0 +1,324 @@
|
||||
/**
|
||||
* 快速操作服务
|
||||
*
|
||||
* 功能：调用Python微服务的预写函数API
|
||||
*
|
||||
* @module QuickActionService
|
||||
*/
|
||||
|
||||
import { logger } from '../../../../common/logging/index.js';
|
||||
import axios from 'axios';
|
||||
|
||||
const PYTHON_SERVICE_URL = process.env.EXTRACTION_SERVICE_URL || 'http://localhost:8000';
|
||||
|
||||
// ==================== 类型定义 ====================
|
||||
|
||||
interface FilterParams {
|
||||
conditions: Array<{
|
||||
column: string;
|
||||
operator: string;
|
||||
value?: any;
|
||||
}>;
|
||||
logic: 'and' | 'or';
|
||||
}
|
||||
|
||||
interface RecodeParams {
|
||||
column: string;
|
||||
mapping: Record<string, any>;
|
||||
createNewColumn: boolean;
|
||||
newColumnName?: string;
|
||||
}
|
||||
|
||||
interface BinningParams {
|
||||
column: string;
|
||||
method: 'custom' | 'equal_width' | 'equal_freq';
|
||||
newColumnName: string;
|
||||
bins?: number[];
|
||||
labels?: (string | number)[];
|
||||
numBins?: number;
|
||||
}
|
||||
|
||||
interface ConditionalParams {
|
||||
newColumnName: string;
|
||||
rules: Array<{
|
||||
conditions: Array<{
|
||||
column: string;
|
||||
operator: string;
|
||||
value: any;
|
||||
}>;
|
||||
logic: 'and' | 'or';
|
||||
result: any;
|
||||
}>;
|
||||
elseValue?: any;
|
||||
}
|
||||
|
||||
interface DropnaParams {
|
||||
method: 'row' | 'column' | 'both';
|
||||
threshold?: number;
|
||||
subset?: string[];
|
||||
}
|
||||
|
||||
interface ComputeParams {
|
||||
newColumnName: string;
|
||||
formula: string;
|
||||
}
|
||||
|
||||
interface PivotParams {
|
||||
indexColumn: string;
|
||||
pivotColumn: string;
|
||||
valueColumns: string[];
|
||||
aggfunc: 'first' | 'last' | 'mean' | 'sum' | 'min' | 'max';
|
||||
}
|
||||
|
||||
interface OperationResult {
|
||||
success: boolean;
|
||||
result_data?: any[];
|
||||
output?: string;
|
||||
execution_time?: number;
|
||||
result_shape?: [number, number];
|
||||
error?: string;
|
||||
}
|
||||
|
||||
// ==================== 服务类 ====================
|
||||
|
||||
export class QuickActionService {
|
||||
|
||||
/**
|
||||
* 执行高级筛选
|
||||
*/
|
||||
async executeFilter(data: any[], params: FilterParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用筛选API: ${params.conditions.length}个条件`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/filter`, {
|
||||
data,
|
||||
conditions: params.conditions,
|
||||
logic: params.logic,
|
||||
}, {
|
||||
timeout: 60000, // 60秒超时
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] 筛选成功: ${response.data.result_shape?.[0] || 0} 行`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] 筛选失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || '筛选失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行数值映射（重编码）
|
||||
*/
|
||||
async executeRecode(data: any[], params: RecodeParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用重编码API: ${params.column}`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/recode`, {
|
||||
data,
|
||||
column: params.column,
|
||||
mapping: params.mapping,
|
||||
create_new_column: params.createNewColumn,
|
||||
new_column_name: params.newColumnName,
|
||||
}, {
|
||||
timeout: 60000,
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] 重编码成功`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] 重编码失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || '重编码失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行分箱
|
||||
*/
|
||||
async executeBinning(data: any[], params: BinningParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用分箱API: ${params.column}, 方法=${params.method}`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/binning`, {
|
||||
data,
|
||||
column: params.column,
|
||||
method: params.method,
|
||||
new_column_name: params.newColumnName,
|
||||
bins: params.bins,
|
||||
labels: params.labels,
|
||||
num_bins: params.numBins,
|
||||
}, {
|
||||
timeout: 60000,
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] 分箱成功`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] 分箱失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || '分箱失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行条件生成列
|
||||
*/
|
||||
async executeConditional(data: any[], params: ConditionalParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用条件生成列API: ${params.newColumnName}, ${params.rules.length}条规则`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/conditional`, {
|
||||
data,
|
||||
new_column_name: params.newColumnName,
|
||||
rules: params.rules,
|
||||
else_value: params.elseValue,
|
||||
}, {
|
||||
timeout: 60000,
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] 条件生成列成功`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] 条件生成列失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || '条件生成列失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行删除缺失值
|
||||
*/
|
||||
async executeDropna(data: any[], params: DropnaParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用删除缺失值API: method=${params.method}, threshold=${params.threshold}`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/dropna`, {
|
||||
data,
|
||||
method: params.method,
|
||||
threshold: params.threshold || 0.5,
|
||||
subset: params.subset,
|
||||
}, {
|
||||
timeout: 60000,
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] 删除缺失值成功`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] 删除缺失值失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || '删除缺失值失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行计算列
|
||||
*/
|
||||
async executeCompute(data: any[], params: ComputeParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用计算列API: ${params.newColumnName}, formula=${params.formula}`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/compute`, {
|
||||
data,
|
||||
new_column_name: params.newColumnName,
|
||||
formula: params.formula,
|
||||
}, {
|
||||
timeout: 60000,
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] 计算列成功`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] 计算列失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || '计算列失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行Pivot（长表→宽表）
|
||||
*/
|
||||
async executePivot(data: any[], params: PivotParams): Promise<OperationResult> {
|
||||
try {
|
||||
logger.info(`[QuickActionService] 调用Pivot API: ${params.indexColumn} × ${params.pivotColumn}`);
|
||||
|
||||
const response = await axios.post(`${PYTHON_SERVICE_URL}/api/operations/pivot`, {
|
||||
data,
|
||||
index_column: params.indexColumn,
|
||||
pivot_column: params.pivotColumn,
|
||||
value_columns: params.valueColumns,
|
||||
aggfunc: params.aggfunc,
|
||||
}, {
|
||||
timeout: 60000,
|
||||
});
|
||||
|
||||
logger.info(`[QuickActionService] Pivot成功`);
|
||||
return response.data;
|
||||
|
||||
} catch (error: any) {
|
||||
logger.error(`[QuickActionService] Pivot失败: ${error.message}`);
|
||||
|
||||
if (error.response?.data) {
|
||||
return error.response.data;
|
||||
}
|
||||
|
||||
return {
|
||||
success: false,
|
||||
error: error.message || 'Pivot失败',
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ==================== 导出单例 ====================
|
||||
|
||||
export const quickActionService = new QuickActionService();
|
||||
|
||||
@@ -71,7 +71,13 @@ export class SessionService {
|
||||
logger.info('[SessionService] 解析Excel文件...');
|
||||
let workbook: xlsx.WorkBook;
|
||||
try {
|
||||
workbook = xlsx.read(fileBuffer, { type: 'buffer' });
|
||||
// ✅ 修复：添加解析选项，保留原始格式
|
||||
workbook = xlsx.read(fileBuffer, {
|
||||
type: 'buffer',
|
||||
raw: true, // 保留原始数据，不做类型推断
|
||||
cellText: false, // 不使用格式化文本
|
||||
cellDates: false, // 日期保持为数字
|
||||
});
|
||||
} catch (error: any) {
|
||||
throw new Error(`Excel文件解析失败: ${error.message}`);
|
||||
}
|
||||
@@ -82,7 +88,11 @@ export class SessionService {
|
||||
}
|
||||
|
||||
const sheet = workbook.Sheets[sheetName];
|
||||
const data = xlsx.utils.sheet_to_json(sheet);
|
||||
// ✅ 修复：使用 defval 选项处理空值，raw 保留原始格式
|
||||
const data = xlsx.utils.sheet_to_json(sheet, {
|
||||
raw: false, // 使用格式化后的字符串值（保留"-"等字符）
|
||||
defval: null, // 空单元格使用 null
|
||||
});
|
||||
|
||||
if (data.length === 0) {
|
||||
throw new Error('Excel文件没有数据');
|
||||
@@ -103,9 +113,15 @@ export class SessionService {
|
||||
await storage.upload(fileKey, fileBuffer);
|
||||
logger.info('[SessionService] OSS上传成功');
|
||||
|
||||
// 5. 保存Session到数据库（只存元数据，符合云原生规范）
|
||||
// 5. ✨ 计算数据统计信息（用于数据探索）
|
||||
logger.info('[SessionService] 计算数据统计信息...');
|
||||
const dataStats = this.calculateDataStats(data, columns);
|
||||
logger.info('[SessionService] 统计信息计算完成');
|
||||
|
||||
// 6. 保存Session到数据库（只存元数据，符合云原生规范）
|
||||
const expiresAt = new Date(Date.now() + SESSION_EXPIRE_MINUTES * 60 * 1000);
|
||||
|
||||
// @ts-ignore - dataStats字段在Prisma生成前可能不存在
|
||||
const session = await prisma.dcToolCSession.create({
|
||||
data: {
|
||||
userId,
|
||||
@@ -116,6 +132,7 @@ export class SessionService {
|
||||
columns: columns, // Prisma会自动转换为JSONB
|
||||
encoding: 'utf-8', // 默认utf-8，后续可扩展检测
|
||||
fileSize: fileBuffer.length,
|
||||
dataStats: JSON.parse(JSON.stringify(dataStats)), // ✨ 存储统计信息（转换为JSON）
|
||||
expiresAt,
|
||||
},
|
||||
});
|
||||
@@ -180,10 +197,18 @@ export class SessionService {
|
||||
const buffer = await storage.download(session.fileKey);
|
||||
|
||||
// 3. 内存解析Excel（不落盘）
|
||||
const workbook = xlsx.read(buffer, { type: 'buffer' });
|
||||
const workbook = xlsx.read(buffer, {
|
||||
type: 'buffer',
|
||||
raw: true,
|
||||
cellText: false,
|
||||
cellDates: false,
|
||||
});
|
||||
const sheetName = workbook.SheetNames[0];
|
||||
const sheet = workbook.Sheets[sheetName];
|
||||
const data = xlsx.utils.sheet_to_json(sheet);
|
||||
const data = xlsx.utils.sheet_to_json(sheet, {
|
||||
raw: false,
|
||||
defval: null,
|
||||
});
|
||||
|
||||
// 4. 返回前100行
|
||||
const previewData = data.slice(0, PREVIEW_ROWS);
|
||||
@@ -218,10 +243,18 @@ export class SessionService {
|
||||
const buffer = await storage.download(session.fileKey);
|
||||
|
||||
// 3. 内存解析Excel
|
||||
const workbook = xlsx.read(buffer, { type: 'buffer' });
|
||||
const workbook = xlsx.read(buffer, {
|
||||
type: 'buffer',
|
||||
raw: true,
|
||||
cellText: false,
|
||||
cellDates: false,
|
||||
});
|
||||
const sheetName = workbook.SheetNames[0];
|
||||
const sheet = workbook.Sheets[sheetName];
|
||||
const data = xlsx.utils.sheet_to_json(sheet);
|
||||
const data = xlsx.utils.sheet_to_json(sheet, {
|
||||
raw: false,
|
||||
defval: null,
|
||||
});
|
||||
|
||||
logger.info(`[SessionService] 完整数据获取成功: ${data.length}行`);
|
||||
|
||||
@@ -312,6 +345,48 @@ export class SessionService {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* ✨ 保存AI处理后的完整数据到OSS
|
||||
*
|
||||
* @param sessionId - Session ID
|
||||
* @param processedData - AI处理后的完整数据
|
||||
*/
|
||||
async saveProcessedData(sessionId: string, processedData: any[]): Promise<void> {
|
||||
try {
|
||||
logger.info(`[SessionService] 保存处理数据: ${sessionId}, 行数=${processedData.length}`);
|
||||
|
||||
// 1. 获取Session信息
|
||||
const session = await this.getSession(sessionId);
|
||||
|
||||
// 2. 将数据转换为Excel Buffer
|
||||
const workbook = xlsx.utils.book_new();
|
||||
const worksheet = xlsx.utils.json_to_sheet(processedData);
|
||||
xlsx.utils.book_append_sheet(workbook, worksheet, 'Sheet1');
|
||||
const buffer = xlsx.write(workbook, { type: 'buffer', bookType: 'xlsx' });
|
||||
|
||||
// 3. 上传到OSS（覆盖原文件，保持fileKey不变）
|
||||
logger.info(`[SessionService] 上传处理后数据到OSS: ${session.fileKey}`);
|
||||
await storage.upload(session.fileKey, buffer);
|
||||
|
||||
// 4. 更新Session元数据
|
||||
const newColumns = Object.keys(processedData[0] || {});
|
||||
await prisma.dcToolCSession.update({
|
||||
where: { id: sessionId },
|
||||
data: {
|
||||
totalRows: processedData.length,
|
||||
totalCols: newColumns.length,
|
||||
columns: newColumns,
|
||||
updatedAt: new Date(),
|
||||
},
|
||||
});
|
||||
|
||||
logger.info(`[SessionService] 处理数据保存成功: ${sessionId}`);
|
||||
} catch (error: any) {
|
||||
logger.error(`[SessionService] 保存处理数据失败: ${error.message}`, { sessionId });
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 清理过期Session（定时任务使用）
|
||||
*
|
||||
@@ -352,6 +427,135 @@ export class SessionService {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* ✨ 计算数据统计信息（用于数据探索）
|
||||
*
|
||||
* @param data - 完整数据数组
|
||||
* @param columns - 列名数组
|
||||
* @returns 统计信息对象
|
||||
*/
|
||||
private calculateDataStats(data: any[], columns: string[]): any {
|
||||
const totalRows = data.length;
|
||||
|
||||
const columnStats = columns.map(col => {
|
||||
// 提取该列的所有值
|
||||
const values = data.map(row => row[col]);
|
||||
|
||||
// 缺失值统计
|
||||
const missingCount = values.filter(v => v === null || v === undefined || v === '' || v === 'NA').length;
|
||||
const missingRate = ((missingCount / totalRows) * 100).toFixed(2) + '%';
|
||||
|
||||
// 唯一值数量
|
||||
const uniqueValues = new Set(values.filter(v => v !== null && v !== undefined && v !== ''));
|
||||
const uniqueCount = uniqueValues.size;
|
||||
|
||||
// 检测数据类型
|
||||
const dataType = this.detectColumnType(values);
|
||||
|
||||
// 如果是数值列，计算均值和中位数
|
||||
let mean: number | null = null;
|
||||
let median: number | null = null;
|
||||
let min: number | null = null;
|
||||
let max: number | null = null;
|
||||
|
||||
if (dataType === 'numeric') {
|
||||
const numericValues = values
|
||||
.filter(v => v !== null && v !== undefined && v !== '' && !isNaN(Number(v)))
|
||||
.map(v => Number(v));
|
||||
|
||||
if (numericValues.length > 0) {
|
||||
mean = numericValues.reduce((a, b) => a + b, 0) / numericValues.length;
|
||||
mean = Math.round(mean * 100) / 100; // 保留2位小数
|
||||
|
||||
const sorted = numericValues.slice().sort((a, b) => a - b);
|
||||
const mid = Math.floor(sorted.length / 2);
|
||||
median = sorted.length % 2 === 0
|
||||
? (sorted[mid - 1] + sorted[mid]) / 2
|
||||
: sorted[mid];
|
||||
median = Math.round(median * 100) / 100;
|
||||
|
||||
min = Math.min(...numericValues);
|
||||
max = Math.max(...numericValues);
|
||||
}
|
||||
}
|
||||
|
||||
// 如果是分类列，统计最常见的值
|
||||
let topValues: Array<{ value: string; count: number }> = [];
|
||||
if (dataType === 'categorical' && uniqueCount <= 20) {
|
||||
const valueCounts: { [key: string]: number } = {};
|
||||
values.forEach(v => {
|
||||
if (v !== null && v !== undefined && v !== '') {
|
||||
const key = String(v);
|
||||
valueCounts[key] = (valueCounts[key] || 0) + 1;
|
||||
}
|
||||
});
|
||||
|
||||
topValues = Object.entries(valueCounts)
|
||||
.map(([value, count]) => ({ value, count }))
|
||||
.sort((a, b) => b.count - a.count)
|
||||
.slice(0, 5); // 只保留前5个
|
||||
}
|
||||
|
||||
return {
|
||||
name: col,
|
||||
missingCount,
|
||||
missingRate,
|
||||
uniqueCount,
|
||||
dataType,
|
||||
...(mean !== null && { mean }),
|
||||
...(median !== null && { median }),
|
||||
...(min !== null && { min }),
|
||||
...(max !== null && { max }),
|
||||
...(topValues.length > 0 && { topValues }),
|
||||
};
|
||||
});
|
||||
|
||||
return {
|
||||
totalRows,
|
||||
totalCols: columns.length,
|
||||
columnStats,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 检测列的数据类型
|
||||
*
|
||||
* @param values - 列值数组
|
||||
* @returns 数据类型：numeric | categorical | datetime | text
|
||||
*/
|
||||
private detectColumnType(values: any[]): string {
|
||||
// 过滤空值
|
||||
const nonNullValues = values.filter(v => v !== null && v !== undefined && v !== '');
|
||||
|
||||
if (nonNullValues.length === 0) {
|
||||
return 'unknown';
|
||||
}
|
||||
|
||||
// 检测数值类型（至少80%是数字）
|
||||
const numericCount = nonNullValues.filter(v => !isNaN(Number(v))).length;
|
||||
if (numericCount / nonNullValues.length >= 0.8) {
|
||||
return 'numeric';
|
||||
}
|
||||
|
||||
// 检测日期类型（至少80%是日期）
|
||||
const dateCount = nonNullValues.filter(v => {
|
||||
const dateStr = String(v);
|
||||
return /^\d{4}-\d{2}-\d{2}/.test(dateStr) || !isNaN(Date.parse(dateStr));
|
||||
}).length;
|
||||
if (dateCount / nonNullValues.length >= 0.8) {
|
||||
return 'datetime';
|
||||
}
|
||||
|
||||
// 检测分类类型（唯一值数量 < 总数的20%）
|
||||
const uniqueCount = new Set(nonNullValues).size;
|
||||
if (uniqueCount < nonNullValues.length * 0.2 && uniqueCount <= 50) {
|
||||
return 'categorical';
|
||||
}
|
||||
|
||||
// 默认为文本类型
|
||||
return 'text';
|
||||
}
|
||||
|
||||
/**
|
||||
* 格式化Session数据
|
||||
*
|
||||
|
||||
Reference in New Issue
Block a user