/**
 * 端到端真实测试 v2 - 简化版
 * 
 * 使用真实数据测试完整流程：
 * 1. 创建项目
 * 2. 导入1篇文献（简化）
 * 3. 创建全文复筛任务
 * 4. 等待LLM处理
 * 5. 查看结果
 */

import axios from 'axios';
import { PrismaClient } from '@prisma/client';
import fs from 'fs/promises';
import path from 'path';

const API_BASE = 'http://localhost:3000/api/v1/asl';
const prisma = new PrismaClient();

interface TestResult {
  projectId?: string;
  literatureIds?: string[];
  taskId?: string;
  success: boolean;
  error?: string;
}

async function runTest(): Promise<TestResult> {
  console.log('🚀 开始端到端真实测试 v2\n');
  console.log('⏰ 测试时间:', new Date().toLocaleString('zh-CN'));
  console.log('📍 API地址:', API_BASE);
  console.log('=' .repeat(80) + '\n');

  const result: TestResult = { success: false };

  try {
    // ========================================
    // Step 1: 创建测试项目
    // ========================================
    console.log('📋 Step 1: 创建测试项目');
    
    const picosPath = path.join(
      process.cwd(),
      '../docs/03-业务模块/ASL-AI智能文献/05-测试文档/03-测试数据/screening/测试案例的PICOS、纳入标准、排除标准.txt'
    );
    
    const picosContent = await fs.readFile(picosPath, 'utf-8');
    
    // 解析PICOS
    const populationMatch = picosContent.match(/P \(Population\)[：:]\s*(.+)/);
    const interventionMatch = picosContent.match(/I \(Intervention\)[：:]\s*(.+)/);
    const comparisonMatch = picosContent.match(/C \(Comparison\)[：:]\s*(.+)/);
    const outcomeMatch = picosContent.match(/O \(Outcome\)[：:]\s*(.+)/);
    const studyDesignMatch = picosContent.match(/S \(Study Design\)[：:]\s*(.+)/);

    const projectData = {
      name: `E2E测试-${Date.now()}`,
      description: '端到端真实测试项目',
      picoCriteria: {
        P: populationMatch?.[1]?.trim() || '缺血性卒中患者',
        I: interventionMatch?.[1]?.trim() || '抗血小板治疗',
        C: comparisonMatch?.[1]?.trim() || '对照组',
        O: outcomeMatch?.[1]?.trim() || '卒中复发',
        S: studyDesignMatch?.[1]?.trim() || 'RCT',
      },
    };

    const projectResponse = await axios.post(`${API_BASE}/projects`, projectData);
    result.projectId = projectResponse.data.data.id;
    console.log(`✅ 项目创建成功: ${result.projectId}\n`);

    // ========================================
    // Step 2: 导入1篇简单测试文献
    // ========================================
    console.log('📚 Step 2: 导入测试文献（使用简化数据）');
    
    const literatureData = {
      projectId: result.projectId,
      literatures: [
        {
          pmid: 'TEST001',
          title: 'Antiplatelet Therapy for Secondary Stroke Prevention: A Randomized Controlled Trial',
          abstract: 'Background: Stroke is a major cause of death worldwide. This study evaluates antiplatelet therapy effectiveness. Methods: We conducted an RCT with 500 patients randomized to aspirin vs clopidogrel groups. The study was double-blind. Results: Primary outcome (stroke recurrence) occurred in 12% of aspirin group vs 8% of clopidogrel group (p=0.03). Secondary outcomes showed similar trends. Conclusion: Clopidogrel demonstrates superior efficacy for secondary stroke prevention in Asian patients.',
          authors: 'Zhang W, Li H, Wang Y',
          journal: 'Stroke Research',
          publicationYear: 2023,
          hasPdf: false,
        },
      ],
    };

    const importResponse = await axios.post(`${API_BASE}/literatures/import`, literatureData);
    console.log(`✅ 文献导入成功: ${importResponse.data.data.importedCount}篇\n`);

    // 获取文献ID
    const literatures = await prisma.aslLiterature.findMany({
      where: { projectId: result.projectId },
      select: { id: true, title: true },
    });
    result.literatureIds = literatures.map(lit => lit.id);
    console.log('📄 导入的文献:');
    literatures.forEach(lit => {
      console.log(`   - ${lit.id.slice(0, 8)}: ${lit.title.slice(0, 60)}...`);
    });
    console.log('');

    // ========================================
    // Step 3: 创建全文复筛任务
    // ========================================
    console.log('🤖 Step 3: 创建全文复筛任务');
    
    const taskData = {
      projectId: result.projectId,
      literatureIds: result.literatureIds,
      config: {
        modelA: 'deepseek-v3',
        modelB: 'qwen-max',
        concurrency: 1,
        skipExtraction: true, // 跳过PDF提取，使用标题+摘要
      },
    };

    const taskResponse = await axios.post(`${API_BASE}/fulltext-screening/tasks`, taskData);
    result.taskId = taskResponse.data.data.taskId;
    console.log(`✅ 任务创建成功: ${result.taskId}\n`);

    // ========================================
    // Step 4: 监控任务进度
    // ========================================
    console.log('⏳ Step 4: 监控任务进度（等待LLM处理）\n');
    
    let maxAttempts = 30; // 最多等待5分钟
    let attempt = 0;
    let taskCompleted = false;

    while (attempt < maxAttempts && !taskCompleted) {
      await new Promise(resolve => setTimeout(resolve, 10000)); // 每10秒查询一次
      attempt++;

      try {
        const progressResponse = await axios.get(
          `${API_BASE}/fulltext-screening/tasks/${result.taskId}/progress`
        );
        const progress = progressResponse.data.data;

        console.log(`[${attempt}/${maxAttempts}] 进度: ${progress.processedCount}/${progress.totalCount} | ` +
                    `成功: ${progress.successCount} | 失败: ${progress.failedCount} | ` +
                    `Token: ${progress.totalTokens} | 成本: ¥${progress.totalCost.toFixed(4)}`);

        if (progress.status === 'completed' || progress.status === 'failed') {
          taskCompleted = true;
          console.log(`\n✅ 任务完成！状态: ${progress.status}\n`);
        }
      } catch (error: any) {
        console.log(`⚠️ 查询进度失败: ${error.message}`);
      }
    }

    if (!taskCompleted) {
      console.log('⚠️ 任务超时，但可能仍在后台处理\n');
    }

    // ========================================
    // Step 5: 获取结果
    // ========================================
    console.log('📊 Step 5: 获取处理结果\n');
    
    try {
      const resultsResponse = await axios.get(
        `${API_BASE}/fulltext-screening/tasks/${result.taskId}/results`
      );
      const results = resultsResponse.data.data;

      console.log('=' .repeat(80));
      console.log('📈 最终统计:');
      console.log(`   - 总文献数: ${results.results.length}`);
      console.log(`   - 总Token: ${results.summary.totalTokens}`);
      console.log(`   - 总成本: ¥${results.summary.totalCost.toFixed(4)}`);
      console.log('');

      if (results.results.length > 0) {
        console.log('📄 文献结果详情:');
        results.results.forEach((r: any, idx: number) => {
          console.log(`\n[${idx + 1}] ${r.literatureTitle}`);
          console.log(`    Model A (${r.modelAName}): ${r.modelAStatus}`);
          console.log(`    Model B (${r.modelBName}): ${r.modelBStatus}`);
          console.log(`    Token: ${r.modelATokens + r.modelBTokens}`);
          console.log(`    成本: ¥${(r.modelACost + r.modelBCost).toFixed(4)}`);
          
          if (r.modelAStatus === 'success' && r.modelAOverall) {
            console.log(`    决策: ${r.modelAOverall.overall_decision || 'N/A'}`);
          }
        });
      }

      result.success = results.results.length > 0;
      
    } catch (error: any) {
      console.log(`❌ 获取结果失败: ${error.message}`);
    }

    console.log('\n' + '=' .repeat(80));
    console.log('🎉 测试完成！\n');

  } catch (error: any) {
    console.error('\n❌ 测试失败:', error.message);
    if (error.response?.data) {
      console.error('错误详情:', JSON.stringify(error.response.data, null, 2));
    }
    result.success = false;
    result.error = error.message;
  } finally {
    await prisma.$disconnect();
  }

  return result;
}

// 运行测试
runTest()
  .then(result => {
    if (result.success) {
      console.log('✅ 端到端测试成功！');
      process.exit(0);
    } else {
      console.log('❌ 端到端测试失败');
      process.exit(1);
    }
  })
  .catch(error => {
    console.error('💥 测试执行异常:', error);
    process.exit(1);
  });