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AIclinicalresearch/backend/test-result.txt
HaHafeng beb7f7f559 feat(asl): Implement full-text screening core LLM service and validation system (Day 1-3) 
Core Components:
- PDFStorageService with Dify/OSS adapters
- LLM12FieldsService with Nougat-first + dual-model + 3-layer JSON parsing
- PromptBuilder for dynamic prompt assembly
- MedicalLogicValidator with 5 rules + fault tolerance
- EvidenceChainValidator for citation integrity
- ConflictDetectionService for dual-model comparison

Prompt Engineering:
- System Prompt (6601 chars, Section-Aware strategy)
- User Prompt template (PICOS context injection)
- JSON Schema (12 fields constraints)
- Cochrane standards (not loaded in MVP)

Key Innovations:
- 3-layer JSON parsing (JSON.parse + json-repair + code block extraction)
- Promise.allSettled for dual-model fault tolerance
- safeGetFieldValue for robust field extraction
- Mixed CN/EN token calculation

Integration Tests:
- integration-test.ts (full test)
- quick-test.ts (quick test)
- cached-result-test.ts (fault tolerance test)

Documentation Updates:
- Development record (Day 2-3 summary)
- Quality assurance strategy (full-text screening)
- Development plan (progress update)
- Module status (v1.1 update)
- Technical debt (10 new items)

Test Results:
- JSON parsing success rate: 100%
- Medical logic validation: 5/5 passed
- Dual-model parallel processing: OK
- Cost per PDF: CNY 0.10

Files: 238 changed, 14383 insertions(+), 32 deletions(-)
Docs: docs/03-涓氬姟妯″潡/ASL-AI鏅鸿兘鏂囩尞/05-寮€鍙戣褰?2025-11-22_Day2-Day3_LLM鏈嶅姟涓庨獙璇佺郴缁熷紑鍙?md
2025-11-22 22:21:12 +08:00

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[dotenv@17.2.3] injecting env (13) from .env -- tip: 👥 sync secrets across teammates & machines: https://dotenvx.com/ops
[Config] Loaded .env file for development
[CacheFactory] Using MemoryCacheAdapter
🚀 开始测试 Day 2 Prompt 和服务...
📋 测试1: PromptBuilder基础功能
────────────────────────────────────────────────────────────
[1.1] 加载基础System Prompt...
2025-11-22 20:12:31.222 [aiclinical-backend] info: Building system prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.224 [aiclinical-backend] info: System prompt loaded from D:\MyCursor\AIclinicalresearch\backend\src\modules\asl\fulltext-screening\prompts\system_prompt.md
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
✅ 成功！长度: 6699 字符
- 包含"Cochrane": ✅
- 包含"Lost in the Middle": ✅
- 包含"逐段阅读": ✅
[1.2] 加载Cochrane标准...
2025-11-22 20:12:31.224 [aiclinical-backend] info: Building system prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.225 [aiclinical-backend] info: Cochrane standard loaded: 随机化方法
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.225 [aiclinical-backend] info: Cochrane standard loaded: 盲法
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.225 [aiclinical-backend] info: Cochrane standard loaded: 结果完整性
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.225 [aiclinical-backend] info: System prompt built successfully, total length: 31538 chars
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
✅ 成功！长度: 31538 字符（增加了 24839 字符）
- 包含"随机化方法": ✅
- 包含"盲法": ✅
- 包含"结果完整性": ✅
[1.3] 加载Few-shot案例...
2025-11-22 20:12:31.225 [aiclinical-backend] info: Building system prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.226 [aiclinical-backend] info: Few-shot example loaded: 信息在中间位置案例
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.226 [aiclinical-backend] info: System prompt built successfully, total length: 14669 chars
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
✅ 成功！长度: 14669 字符
- 包含"信息在中间位置": ✅
[1.4] MVP完整配置（Cochrane + Few-shot）...
2025-11-22 20:12:31.226 [aiclinical-backend] info: Building system prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.226 [aiclinical-backend] info: System prompt built successfully, total length: 39508 chars
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
✅ 成功！长度: 39508 字符
- 预估Token: 13169
[1.5] 加载JSON Schema...
✅ 成功！
- 类型: object
- 必需字段: fields, processing_log, verification, metadata
- 12字段: ✅
[1.6] 构建User Prompt...
2025-11-22 20:12:31.226 [aiclinical-backend] info: Building user prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.227 [aiclinical-backend] info: User prompt template loaded from D:\MyCursor\AIclinicalresearch\backend\src\modules\asl\fulltext-screening\prompts\user_prompt_template.md
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.227 [aiclinical-backend] info: User prompt built successfully, total length: 4425 chars
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
✅ 成功！长度: 4425 字符
- 包含PICOS: ✅
- 包含全文: ✅
[1.7] 构建完整Prompt（System + User）...
2025-11-22 20:12:31.227 [aiclinical-backend] info: Building system prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.227 [aiclinical-backend] info: Building user prompt...
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.227 [aiclinical-backend] info: User prompt built successfully, total length: 4425 chars
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
2025-11-22 20:12:31.227 [aiclinical-backend] info: System prompt built successfully, total length: 39508 chars
{
"env": "development",
"instance": "LAPTOP-UH2VURTB",
"pid": 53216
}
✅ 成功！
- System Prompt: 39508 字符
- User Prompt: 4425 字符
- 总计: 43933 字符
- 预估Token: 14644
💾 完整Prompt已保存到: D:\MyCursor\AIclinicalresearch\backend\test-output/
✅ PromptBuilder测试全部通过！
📋 测试2: LLM12FieldsService（模拟模式）
────────────────────────────────────────────────────────────
[2.1] 创建LLM12FieldsService实例...
✅ 成功！
[2.2] 测试Nougat提取策略...
⏭️ 跳过（需要实际PDF文件）
[2.3] 测试缓存Key生成...
✅ 缓存机制已集成（通过process12Fields验证）
[2.4] 测试成本计算...
测试Token数: 10000
- deepseek-v3: ¥0.0100
- qwen-max: ¥0.0400
- gpt-4o: ¥0.3000
✅ 成本计算逻辑正确
✅ LLM12FieldsService测试完成（模拟模式）！
⚠️ 注意: 实际LLM调用需要：
1. 配置API Key（DeepSeek/Qwen）
2. 准备测试PDF文件
3. 运行集成测试
📋 测试3: Prompt文件完整性检查
────────────────────────────────────────────────────────────
检查必需文件:
✅ system_prompt.md
大小: 10KB
✅ user_prompt_template.md
大小: 5KB
✅ json_schema.json
大小: 14KB
✅ cochrane_standards/随机化方法.md
大小: 8KB
✅ cochrane_standards/盲法.md
大小: 11KB
✅ cochrane_standards/结果完整性.md
大小: 12KB
✅ few_shot_examples/信息在中间位置案例.md
大小: 10KB
✅ 所有必需文件都存在！
============================================================
🎉 所有测试完成！Day 2 Prompt和服务验证通过！
============================================================
📋 下一步建议:
1. 查看生成的Prompt文件（test-output/目录）
2. 配置API Key准备集成测试
3. 继续Day 3开发（验证服务）
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