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
29 lines
671 B
TypeScript
29 lines
671 B
TypeScript
import XLSX from 'xlsx';
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const filePath = 'D:\\MyCursor\\AIclinicalresearch\\docs\\03-业务模块\\ASL-AI智能文献\\05-测试文档\\03-测试数据\\screening\\Test Cases.xlsx';
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const workbook = XLSX.readFile(filePath);
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const sheetName = workbook.SheetNames[0];
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const worksheet = workbook.Sheets[sheetName];
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const data = XLSX.utils.sheet_to_json(worksheet);
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console.log(`总行数: ${data.length}`);
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console.log('\n前3行数据:');
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data.slice(0, 3).forEach((row: any, i) => {
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console.log(`\n第${i+1}行:`);
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console.log(JSON.stringify(row, null, 2));
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});
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console.log('\n所有列名:');
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if (data.length > 0) {
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console.log(Object.keys(data[0]));
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}
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