refactor(asl): ASL frontend architecture refactoring with left navigation
- feat: Create ASLLayout component with 7-module left navigation - feat: Implement Title Screening Settings page with optimized PICOS layout - feat: Add placeholder pages for Workbench and Results - fix: Fix nested routing structure for React Router v6 - fix: Resolve Spin component warning in MainLayout - fix: Add QueryClientProvider to App.tsx - style: Optimize PICOS form layout (P+I left, C+O+S right) - style: Align Inclusion/Exclusion criteria side-by-side - docs: Add architecture refactoring and routing fix reports Ref: Week 2 Frontend Development Scope: ASL module MVP - Title Abstract Screening
This commit is contained in:
359
backend/src/scripts/test-closeai.ts
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359
backend/src/scripts/test-closeai.ts
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/**
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* CloseAI集成测试脚本
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*
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* 测试通过CloseAI代理访问GPT-5和Claude-4.5模型
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*
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* 运行方式：
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* ```bash
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* cd backend
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* npx tsx src/scripts/test-closeai.ts
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* ```
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*
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* 环境变量要求：
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* - CLOSEAI_API_KEY: CloseAI API密钥
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* - CLOSEAI_OPENAI_BASE_URL: OpenAI端点
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* - CLOSEAI_CLAUDE_BASE_URL: Claude端点
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*
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* 参考文档：docs/02-通用能力层/01-LLM大模型网关/03-CloseAI集成指南.md
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*/
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import { LLMFactory } from '../common/llm/adapters/LLMFactory.js';
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import { config } from '../config/env.js';
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/**
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* 测试配置验证
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*/
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function validateConfig() {
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console.log('🔍 验证环境配置...\n');
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const checks = [
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{
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name: 'CLOSEAI_API_KEY',
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value: config.closeaiApiKey,
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required: true,
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},
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{
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name: 'CLOSEAI_OPENAI_BASE_URL',
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value: config.closeaiOpenaiBaseUrl,
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required: true,
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},
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{
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name: 'CLOSEAI_CLAUDE_BASE_URL',
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value: config.closeaiClaudeBaseUrl,
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required: true,
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},
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];
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let allValid = true;
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for (const check of checks) {
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const status = check.value ? '✅' : '❌';
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console.log(`${status} ${check.name}: ${check.value ? '已配置' : '未配置'}`);
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if (check.required && !check.value) {
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allValid = false;
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}
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}
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console.log('');
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if (!allValid) {
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throw new Error('环境配置不完整，请检查 .env 文件');
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}
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console.log('✅ 环境配置验证通过\n');
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}
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/**
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* 测试GPT-5-Pro
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*/
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async function testGPT5() {
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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console.log('1️⃣ 测试 GPT-5-Pro');
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n');
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try {
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const gpt5 = LLMFactory.getAdapter('gpt-5');
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console.log('📤 发送测试请求...');
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console.log('提示词: "你好，请用一句话介绍你自己。"\n');
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const startTime = Date.now();
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const response = await gpt5.chat([
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{
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role: 'user',
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content: '你好，请用一句话介绍你自己。',
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},
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]);
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const duration = Date.now() - startTime;
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console.log('📥 收到响应:\n');
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console.log(`模型: ${response.model}`);
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console.log(`内容: ${response.content}`);
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console.log(`耗时: ${duration}ms`);
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if (response.usage) {
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console.log(`Token使用: ${response.usage.totalTokens} (输入: ${response.usage.promptTokens}, 输出: ${response.usage.completionTokens})`);
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}
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console.log('\n✅ GPT-5测试通过\n');
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return true;
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} catch (error) {
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console.error('\n❌ GPT-5测试失败:', error);
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return false;
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}
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}
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/**
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* 测试Claude-4.5-Sonnet
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*/
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async function testClaude() {
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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console.log('2️⃣ 测试 Claude-4.5-Sonnet');
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n');
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try {
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const claude = LLMFactory.getAdapter('claude-4.5');
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console.log('📤 发送测试请求...');
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console.log('提示词: "你好，请用一句话介绍你自己。"\n');
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const startTime = Date.now();
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const response = await claude.chat([
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{
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role: 'user',
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content: '你好，请用一句话介绍你自己。',
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},
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]);
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const duration = Date.now() - startTime;
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console.log('📥 收到响应:\n');
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console.log(`模型: ${response.model}`);
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console.log(`内容: ${response.content}`);
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console.log(`耗时: ${duration}ms`);
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if (response.usage) {
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console.log(`Token使用: ${response.usage.totalTokens} (输入: ${response.usage.promptTokens}, 输出: ${response.usage.completionTokens})`);
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}
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console.log('\n✅ Claude测试通过\n');
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return true;
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} catch (error) {
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console.error('\n❌ Claude测试失败:', error);
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return false;
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}
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}
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/**
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* 测试文献筛选场景（实际应用）
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*/
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async function testLiteratureScreening() {
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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console.log('3️⃣ 测试文献筛选场景（双模型对比）');
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n');
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const testLiterature = {
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title: 'Deep learning in medical imaging: A systematic review',
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abstract: 'Background: Deep learning has shown remarkable performance in various medical imaging tasks. Methods: We systematically reviewed 150 studies on deep learning applications in radiology, pathology, and ophthalmology. Results: Deep learning models achieved high accuracy (>90%) in most tasks. Conclusion: Deep learning is a promising tool for medical image analysis.',
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};
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const picoPrompt = `
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请根据以下PICO标准，判断这篇文献是否应该纳入系统评价：
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**PICO标准：**
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- Population: 成年患者
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- Intervention: 深度学习模型
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- Comparison: 传统机器学习方法
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- Outcome: 诊断准确率
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**文献信息：**
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标题：${testLiterature.title}
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摘要：${testLiterature.abstract}
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请输出JSON格式：
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{
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"decision": "include/exclude/uncertain",
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"reason": "判断理由",
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"confidence": 0.0-1.0
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}
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`;
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try {
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console.log('📤 使用DeepSeek和GPT-5进行双模型对比筛选...\n');
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// 并行调用两个模型
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const [deepseekAdapter, gpt5Adapter] = [
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LLMFactory.getAdapter('deepseek-v3'),
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LLMFactory.getAdapter('gpt-5'),
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];
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const startTime = Date.now();
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const [deepseekResponse, gpt5Response] = await Promise.all([
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deepseekAdapter.chat([{ role: 'user', content: picoPrompt }]),
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gpt5Adapter.chat([{ role: 'user', content: picoPrompt }]),
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]);
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const duration = Date.now() - startTime;
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console.log('📥 DeepSeek响应:');
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console.log(deepseekResponse.content);
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console.log('');
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console.log('📥 GPT-5响应:');
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console.log(gpt5Response.content);
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console.log('');
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console.log(`⏱️ 总耗时: ${duration}ms（并行）`);
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console.log(`💰 总Token: ${(deepseekResponse.usage?.totalTokens || 0) + (gpt5Response.usage?.totalTokens || 0)}`);
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// 尝试解析JSON结果（简单验证）
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try {
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const deepseekDecision = JSON.parse(deepseekResponse.content);
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const gpt5Decision = JSON.parse(gpt5Response.content);
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console.log('\n✅ 双模型筛选结果:');
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console.log(`DeepSeek决策: ${deepseekDecision.decision} (置信度: ${deepseekDecision.confidence})`);
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console.log(`GPT-5决策: ${gpt5Decision.decision} (置信度: ${gpt5Decision.confidence})`);
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if (deepseekDecision.decision === gpt5Decision.decision) {
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console.log('✅ 两个模型一致，共识度高');
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} else {
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console.log('⚠️ 两个模型不一致，建议人工复核或启用第三方仲裁（Claude）');
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}
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} catch (parseError) {
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console.log('⚠️ JSON解析失败（测试环境，实际应用需要优化提示词）');
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}
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console.log('\n✅ 文献筛选场景测试通过\n');
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return true;
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} catch (error) {
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console.error('\n❌ 文献筛选场景测试失败:', error);
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return false;
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}
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}
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/**
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* 测试流式调用（可选）
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*/
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async function testStreamMode() {
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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console.log('4️⃣ 测试流式调用（GPT-5）');
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n');
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try {
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const gpt5 = LLMFactory.getAdapter('gpt-5');
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console.log('📤 发送流式请求...');
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console.log('提示词: "请写一首关于人工智能的短诗（4行）"\n');
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console.log('📥 流式响应:\n');
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const startTime = Date.now();
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let fullContent = '';
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let chunkCount = 0;
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for await (const chunk of gpt5.chatStream([
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{
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role: 'user',
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content: '请写一首关于人工智能的短诗（4行）',
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},
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])) {
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if (chunk.content) {
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process.stdout.write(chunk.content);
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fullContent += chunk.content;
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chunkCount++;
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}
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if (chunk.done) {
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const duration = Date.now() - startTime;
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console.log('\n');
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console.log(`\n⏱️ 耗时: ${duration}ms`);
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console.log(`📦 Chunk数: ${chunkCount}`);
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console.log(`📝 总字符数: ${fullContent.length}`);
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if (chunk.usage) {
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console.log(`💰 Token使用: ${chunk.usage.totalTokens}`);
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}
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}
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}
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console.log('\n✅ 流式调用测试通过\n');
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return true;
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} catch (error) {
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console.error('\n❌ 流式调用测试失败:', error);
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return false;
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}
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}
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/**
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* 主测试函数
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*/
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async function main() {
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console.log('╔═══════════════════════════════════════════════════╗');
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console.log('║ 🧪 CloseAI集成测试 ║');
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console.log('║ 测试GPT-5和Claude-4.5通过CloseAI代理访问 ║');
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console.log('╚═══════════════════════════════════════════════════╝\n');
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try {
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// 验证配置
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validateConfig();
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// 测试结果
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const results = {
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gpt5: false,
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claude: false,
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literatureScreening: false,
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stream: false,
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};
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// 1. 测试GPT-5
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results.gpt5 = await testGPT5();
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// 2. 测试Claude-4.5
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results.claude = await testClaude();
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// 3. 测试文献筛选场景
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results.literatureScreening = await testLiteratureScreening();
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// 4. 测试流式调用（可选）
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results.stream = await testStreamMode();
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// 总结
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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console.log('📊 测试总结');
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n');
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const allPassed = Object.values(results).every((r) => r === true);
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console.log(`GPT-5测试: ${results.gpt5 ? '✅ 通过' : '❌ 失败'}`);
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console.log(`Claude测试: ${results.claude ? '✅ 通过' : '❌ 失败'}`);
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console.log(`文献筛选场景: ${results.literatureScreening ? '✅ 通过' : '❌ 失败'}`);
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console.log(`流式调用测试: ${results.stream ? '✅ 通过' : '❌ 失败'}`);
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console.log('\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n');
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if (allPassed) {
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console.log('🎉 所有测试通过！CloseAI集成成功！');
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console.log('\n✅ 可以在ASL模块中使用GPT-5和Claude-4.5进行双模型对比筛选');
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console.log('✅ 支持三模型共识仲裁（DeepSeek + GPT-5 + Claude）');
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console.log('✅ 支持流式调用，适用于实时响应场景\n');
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process.exit(0);
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} else {
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console.error('⚠️ 部分测试失败，请检查配置和网络连接\n');
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process.exit(1);
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}
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} catch (error) {
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console.error('❌ 测试执行失败:', error);
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process.exit(1);
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}
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}
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// 运行测试
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main();
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Reference in New Issue
Block a user