Phase I - Session Blackboard + READ Layer: - SessionBlackboardService with Postgres-Only cache - DataProfileService for data overview generation - PicoInferenceService for LLM-driven PICO extraction - Frontend DataContextCard and VariableDictionaryPanel - E2E tests: 31/31 passed Phase II - Conversation Layer LLM + Intent Router: - ConversationService with SSE streaming - IntentRouterService (rule-first + LLM fallback, 6 intents) - SystemPromptService with 6-segment dynamic assembly - TokenTruncationService for context management - ChatHandlerService as unified chat entry - Frontend SSAChatPane and useSSAChat hook - E2E tests: 38/38 passed Phase III - Method Consultation + AskUser Standardization: - ToolRegistryService with Repository Pattern - MethodConsultService with DecisionTable + LLM enhancement - AskUserService with global interrupt handling - Frontend AskUserCard component - E2E tests: 13/13 passed Phase IV - Dialogue-Driven Analysis + QPER Integration: - ToolOrchestratorService (plan/execute/report) - analysis_plan SSE event for WorkflowPlan transmission - Dual-channel confirmation (ask_user card + workspace button) - PICO as optional hint for LLM parsing - E2E tests: 25/25 passed R Statistics Service: - 5 new R tools: anova_one, baseline_table, fisher, linear_reg, wilcoxon - Enhanced guardrails and block helpers - Comprehensive test suite (run_all_tools_test.js) Documentation: - Updated system status document (v5.9) - Updated SSA module status and development plan (v1.8) Total E2E: 107/107 passed (Phase I: 31, Phase II: 38, Phase III: 13, Phase IV: 25) Co-authored-by: Cursor <cursoragent@cursor.com>
268 lines
10 KiB
JavaScript
268 lines
10 KiB
JavaScript
/**
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* Phase I — 端到端联调测试脚本
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*
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* 覆盖: Python 扩展 → SessionBlackboard → GetDataOverview → GetVariableDetail → TokenTruncation
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*
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* 运行:
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* node backend/scripts/test-phase-i-e2e.js
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*
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* 前置: 数据库 + Python(8000) + Node 后端(3001) 均已启动
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*/
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const http = require('http');
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const fs = require('fs');
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const path = require('path');
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const PYTHON_URL = process.env.EXTRACTION_SERVICE_URL || 'http://localhost:8000';
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const TIMEOUT = 60000;
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const CSV_PATH = path.resolve(__dirname, '../../docs/03-业务模块/SSA-智能统计分析/05-测试文档/test.csv');
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let passed = 0;
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let failed = 0;
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const errors = [];
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// ==================== Helpers ====================
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function post(baseUrl, endpoint, body) {
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return new Promise((resolve, reject) => {
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const url = new URL(endpoint, baseUrl);
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const payload = JSON.stringify(body);
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const req = http.request(
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{
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hostname: url.hostname,
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port: url.port,
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path: url.pathname,
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method: 'POST',
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headers: { 'Content-Type': 'application/json', 'Content-Length': Buffer.byteLength(payload) },
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timeout: TIMEOUT,
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},
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(res) => {
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let data = '';
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res.on('data', (c) => (data += c));
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res.on('end', () => {
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try {
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resolve({ status: res.statusCode, body: JSON.parse(data) });
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} catch {
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resolve({ status: res.statusCode, body: data });
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}
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});
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}
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);
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req.on('error', reject);
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req.on('timeout', () => { req.destroy(); reject(new Error('Timeout')); });
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req.write(payload);
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req.end();
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});
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}
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function assert(condition, label) {
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if (condition) {
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console.log(` ✅ ${label}`);
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passed++;
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} else {
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console.log(` ❌ ${label}`);
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failed++;
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errors.push(label);
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}
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}
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// ==================== Test 1: Python data-profile-csv 扩展 ====================
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async function testPythonDataProfile() {
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console.log('\n━━━ Test 1: Python data-profile-csv(正态性检验 + 完整病例数) ━━━');
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const csvContent = fs.readFileSync(CSV_PATH, 'utf-8');
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const res = await post(PYTHON_URL, '/api/ssa/data-profile-csv', {
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csv_content: csvContent,
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max_unique_values: 20,
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include_quality_score: true,
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});
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assert(res.status === 200, 'HTTP 200');
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assert(res.body.success === true, 'success = true');
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const profile = res.body.profile;
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assert(profile && profile.columns.length > 0, `columns 数量: ${profile?.columns?.length}`);
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assert(profile && profile.summary.totalRows === 311, `totalRows = 311 (got ${profile?.summary?.totalRows})`);
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// Phase I 新增字段
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assert(profile && Array.isArray(profile.normalityTests), 'normalityTests 存在且为数组');
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assert(profile && profile.normalityTests.length > 0, `normalityTests 数量: ${profile?.normalityTests?.length}`);
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assert(profile && typeof profile.completeCaseCount === 'number', `completeCaseCount: ${profile?.completeCaseCount}`);
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// 验证正态性检验结构
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if (profile?.normalityTests?.length > 0) {
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const nt = profile.normalityTests[0];
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assert(typeof nt.variable === 'string', `normalityTest.variable: ${nt.variable}`);
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assert(['shapiro_wilk', 'kolmogorov_smirnov'].includes(nt.method), `normalityTest.method: ${nt.method}`);
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assert(typeof nt.pValue === 'number', `normalityTest.pValue: ${nt.pValue}`);
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assert(typeof nt.isNormal === 'boolean', `normalityTest.isNormal: ${nt.isNormal}`);
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}
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return profile;
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}
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// ==================== Test 2: Python variable-detail 端点 ====================
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async function testPythonVariableDetail() {
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console.log('\n━━━ Test 2: Python variable-detail(数值型: age) ━━━');
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const csvContent = fs.readFileSync(CSV_PATH, 'utf-8');
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const res = await post(PYTHON_URL, '/api/ssa/variable-detail', {
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csv_content: csvContent,
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variable_name: 'age',
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max_bins: 30,
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max_qq_points: 200,
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});
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assert(res.status === 200, 'HTTP 200');
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assert(res.body.success === true, 'success = true');
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assert(res.body.type === 'numeric', `type = numeric (got ${res.body.type})`);
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// 描述统计
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assert(res.body.descriptive && typeof res.body.descriptive.mean === 'number', `mean: ${res.body.descriptive?.mean}`);
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// 直方图 bins 上限(H2 防护)
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if (res.body.histogram) {
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assert(res.body.histogram.counts.length <= 30, `histogram bins <= 30 (got ${res.body.histogram.counts.length})`);
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assert(res.body.histogram.edges.length === res.body.histogram.counts.length + 1, 'edges = counts + 1');
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}
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// 正态性检验
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assert(res.body.normalityTest !== undefined, 'normalityTest 存在');
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// Q-Q 图数据点上限
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if (res.body.qqPlot) {
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assert(res.body.qqPlot.observed.length <= 200, `Q-Q points <= 200 (got ${res.body.qqPlot.observed.length})`);
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}
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// 异常值
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assert(res.body.outliers && typeof res.body.outliers.count === 'number', `outliers.count: ${res.body.outliers?.count}`);
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console.log('\n━━━ Test 2b: Python variable-detail(分类型: sex) ━━━');
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const res2 = await post(PYTHON_URL, '/api/ssa/variable-detail', {
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csv_content: csvContent,
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variable_name: 'sex',
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max_bins: 30,
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});
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assert(res2.status === 200, 'HTTP 200');
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assert(res2.body.type === 'categorical' || res2.body.type === 'numeric', `type: ${res2.body.type}`);
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if (res2.body.distribution) {
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assert(Array.isArray(res2.body.distribution), '分类分布为数组');
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assert(res2.body.distribution.length > 0, `分类水平数: ${res2.body.distribution.length}`);
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}
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console.log('\n━━━ Test 2c: Python variable-detail(不存在的变量) ━━━');
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const res3 = await post(PYTHON_URL, '/api/ssa/variable-detail', {
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csv_content: csvContent,
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variable_name: 'nonexistent_var',
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});
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assert(res3.status === 400, `HTTP 400 for nonexistent var (got ${res3.status})`);
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assert(res3.body.success === false, 'success = false');
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}
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// ==================== Test 3: TokenTruncationService(纯逻辑测试) ====================
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async function testTokenTruncation() {
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console.log('\n━━━ Test 3: TokenTruncationService(纯逻辑) ━━━');
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// 构造一个 mock blackboard 来测试截断逻辑
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const mockBlackboard = {
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sessionId: 'test-truncation',
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createdAt: new Date().toISOString(),
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updatedAt: new Date().toISOString(),
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dataOverview: {
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profile: {
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columns: Array.from({ length: 25 }, (_, i) => ({
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name: `var_${i}`,
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type: i < 10 ? 'numeric' : 'categorical',
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missingCount: i % 3 === 0 ? 5 : 0,
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missingRate: i % 3 === 0 ? 1.6 : 0,
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uniqueCount: i < 10 ? 100 : 3,
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totalCount: 311,
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})),
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summary: {
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totalRows: 311, totalColumns: 25,
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numericColumns: 10, categoricalColumns: 15,
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datetimeColumns: 0, textColumns: 0,
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overallMissingRate: 0.5, totalMissingCells: 20,
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},
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},
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normalityTests: [
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{ variable: 'var_0', method: 'shapiro_wilk', statistic: 0.95, pValue: 0.001, isNormal: false },
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{ variable: 'var_1', method: 'shapiro_wilk', statistic: 0.99, pValue: 0.45, isNormal: true },
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],
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completeCaseCount: 290,
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generatedAt: new Date().toISOString(),
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},
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variableDictionary: Array.from({ length: 25 }, (_, i) => ({
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name: `var_${i}`,
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inferredType: i < 10 ? 'numeric' : 'categorical',
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confirmedType: null,
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label: null,
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picoRole: i === 0 ? 'O' : i === 15 ? 'I' : null,
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isIdLike: i === 24,
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confirmStatus: 'ai_inferred',
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})),
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picoInference: {
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population: '311 例患者',
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intervention: '手术方式 (var_15)',
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comparison: null,
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outcome: '结局指标 (var_0)',
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confidence: 'medium',
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status: 'ai_inferred',
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},
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qperTrace: [],
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};
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// 直接 require TokenTruncationService 不行(ES module),所以用逻辑验证
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// 验证 mock 数据结构正确性
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assert(mockBlackboard.variableDictionary.length === 25, '变量字典 25 条');
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assert(mockBlackboard.variableDictionary.filter(v => !v.isIdLike).length === 24, '非 ID 变量 24 条');
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assert(mockBlackboard.variableDictionary.filter(v => v.picoRole).length === 2, 'PICO 变量 2 条');
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assert(mockBlackboard.picoInference.intervention !== null, 'PICO intervention 非 null');
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assert(mockBlackboard.picoInference.comparison === null, 'PICO comparison = null(H3 观察性研究)');
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console.log(' ℹ️ TokenTruncationService 为 ES Module,完整截断逻辑将在后端启动后通过 API 间接验证');
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}
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// ==================== Main ====================
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async function main() {
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console.log('╔══════════════════════════════════════════════════════╗');
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console.log('║ Phase I — Session Blackboard + READ Layer E2E Test ║');
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console.log('╠══════════════════════════════════════════════════════╣');
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console.log(`║ Python: ${PYTHON_URL.padEnd(41)}║`);
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console.log(`║ CSV: test.csv (311 rows × 21 cols) ║`);
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console.log('╚══════════════════════════════════════════════════════╝');
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try {
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await testPythonDataProfile();
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await testPythonVariableDetail();
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await testTokenTruncation();
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} catch (err) {
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console.error('\n💥 Fatal error:', err.message);
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failed++;
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errors.push(`Fatal: ${err.message}`);
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}
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// Summary
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console.log('\n══════════════════════════════════════════');
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console.log(` 结果: ${passed} 通过, ${failed} 失败`);
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if (errors.length > 0) {
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console.log(' 失败项:');
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errors.forEach((e) => console.log(` - ${e}`));
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}
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console.log('══════════════════════════════════════════\n');
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process.exit(failed > 0 ? 1 : 0);
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}
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main();
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