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

backend/scripts/verify-llm-models.ts

@@ -0,0 +1,99 @@
+/**
+ * LLM模型验证脚本
+ * 用于验证实际接入的是哪个版本的模型
+ */
+
+import { LLMFactory } from '../src/common/llm/adapters/LLMFactory.js';
+import { logger } from '../src/common/logging/index.js';
+
+const TEST_PROMPT = "请用一句话简单介绍你自己，包括你的模型名称和版本。";
+
+async function verifyModel(modelType: string, expectedModel: string) {
+  console.log(`\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━`);
+  console.log(`🔍 验证模型: ${modelType}`);
+  console.log(`━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━`);
+  
+  try {
+    const adapter = LLMFactory.getAdapter(modelType as any);
+    console.log(`✅ 适配器创建成功`);
+    console.log(`   模型名称: ${adapter.modelName}`);
+    console.log(`   期望模型: ${expectedModel}`);
+    console.log(`   匹配状态: ${adapter.modelName === expectedModel ? '✅ 正确' : '❌ 不匹配'}`);
+    
+    console.log(`\n🚀 发送测试请求...`);
+    const startTime = Date.now();
+    
+    const response = await adapter.chat([
+      { role: 'user', content: TEST_PROMPT }
+    ]);
+    
+    const duration = Date.now() - startTime;
+    
+    console.log(`\n📊 响应结果:`);
+    console.log(`   实际返回模型: ${response.model}`);
+    console.log(`   响应时间: ${duration}ms`);
+    console.log(`   Token使用:`);
+    console.log(`     - 输入: ${response.usage?.promptTokens || 0}`);
+    console.log(`     - 输出: ${response.usage?.completionTokens || 0}`);
+    console.log(`     - 总计: ${response.usage?.totalTokens || 0}`);
+    console.log(`\n💬 模型回复:`);
+    console.log(`   "${response.content}"`);
+    
+    // 验证是否匹配
+    if (response.model === expectedModel) {
+      console.log(`\n✅ 验证通过！实际调用的就是 ${expectedModel}`);
+      return true;
+    } else {
+      console.log(`\n⚠️  警告！期望 ${expectedModel}，实际返回 ${response.model}`);
+      return false;
+    }
+    
+  } catch (error) {
+    console.error(`\n❌ 验证失败:`, error);
+    return false;
+  }
+}
+
+async function main() {
+  console.log('\n🔬 ASL模块LLM模型验证工具');
+  console.log('=' .repeat(60));
+  console.log('用途: 验证实际接入的模型版本是否正确\n');
+  
+  const models = [
+    { type: 'deepseek-v3', expected: 'deepseek-chat', description: 'DeepSeek-V3' },
+    { type: 'qwen3-72b', expected: 'qwen-max', description: 'Qwen最新最强模型' },
+  ];
+  
+  const results: { model: string; passed: boolean }[] = [];
+  
+  for (const model of models) {
+    const passed = await verifyModel(model.type, model.expected);
+    results.push({ model: model.description, passed });
+    
+    // 避免API限流
+    await new Promise(resolve => setTimeout(resolve, 2000));
+  }
+  
+  // 总结
+  console.log('\n\n' + '='.repeat(60));
+  console.log('📊 验证总结');
+  console.log('='.repeat(60));
+  
+  results.forEach(r => {
+    console.log(`${r.passed ? '✅' : '❌'} ${r.model}: ${r.passed ? '通过' : '未通过'}`);
+  });
+  
+  const allPassed = results.every(r => r.passed);
+  
+  if (allPassed) {
+    console.log('\n🎉 所有模型验证通过！');
+  } else {
+    console.log('\n⚠️  部分模型验证未通过，请检查配置！');
+  }
+  
+  console.log('='.repeat(60) + '\n');
+}
+
+main().catch(console.error);
+
+