HaHafeng
40c2f8e148
Major Features: - Created ekb_schema (13th schema) with 3 tables: KB/Document/Chunk - Implemented EmbeddingService (text-embedding-v4, 1024-dim vectors) - Implemented ChunkService (smart Markdown chunking) - Implemented VectorSearchService (multi-query + hybrid search) - Implemented RerankService (qwen3-rerank) - Integrated DeepSeek V3 QueryRewriter for cross-language search - Python service: Added pymupdf4llm for PDF-to-Markdown conversion - PKB: Dual-mode adapter (pgvector/dify/hybrid) Architecture: - Brain-Hand Model: Business layer (DeepSeek) + Engine layer (pgvector) - Cross-language support: Chinese query matches English documents - Small Embedding (1024) + Strong Reranker strategy Performance: - End-to-end latency: 2.5s - Cost per query: 0.0025 RMB - Accuracy improvement: +20.5% (cross-language) Tests: - test-embedding-service.ts: Vector embedding verified - test-rag-e2e.ts: Full pipeline tested - test-rerank.ts: Rerank quality validated - test-query-rewrite.ts: Cross-language search verified - test-pdf-ingest.ts: Real PDF document tested (Dongen 2003.pdf) Documentation: - Added 05-RAG-Engine-User-Guide.md - Added 02-Document-Processing-User-Guide.md - Updated system status documentation Status: Production ready
155 lines
1.8 KiB
Markdown
155 lines
1.8 KiB
Markdown
# 🚀 快速开始 - 1分钟运行测试
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## Windows用户
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### 方法1：双击运行（最简单）
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1. 双击 `run_tests.bat`
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2. 等待测试完成
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### 方法2：命令行
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```cmd
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cd AIclinicalresearch\tests
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run_tests.bat
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```
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---
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## Linux/Mac用户
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```bash
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cd AIclinicalresearch/tests
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chmod +x run_tests.sh
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./run_tests.sh
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```
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---
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## ⚠️ 前提条件
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**必须先启动Python服务！**
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```bash
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# 打开新终端
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cd AIclinicalresearch/extraction_service
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python main.py
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```
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看到这行表示启动成功：
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```
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INFO: Application startup complete.
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INFO: Uvicorn running on http://0.0.0.0:8001
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```
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---
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## 📊 预期结果
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✅ **全部通过**：
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```
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总测试数: 18
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✅ 通过: 18
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❌ 失败: 0
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通过率: 100.0%
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🎉 所有测试通过！
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```
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⚠️ **部分失败**：
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- 查看红色错误信息
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- 检查失败的具体测试
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- 查看Python服务日志
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---
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## 🎯 测试内容
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- ✅ 6种简单填补方法（均值、中位数、众数、固定值、前向填充、后向填充）
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- ✅ MICE多重插补（单列、多列）
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- ✅ 边界情况（100%缺失、0%缺失、特殊字符）
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- ✅ 各种数据类型（数值、分类、混合）
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- ✅ 性能测试（1000行数据）
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---
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## 💡 提示
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- **第一次运行**会自动安装依赖（pandas, numpy, requests）
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- **测试时间**约 45-60 秒
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- **测试数据**自动生成，无需手动准备
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- **颜色输出**：绿色=通过，红色=失败，黄色=警告
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---
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## 🆘 遇到问题？
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### 问题1：无法连接到服务
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**解决**：确保Python服务在运行（`python main.py`）
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### 问题2：依赖安装失败
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**解决**：手动安装 `pip install pandas numpy requests`
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### 问题3：测试失败
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**解决**：查看错误信息，检查代码逻辑
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---
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**准备好了吗？启动服务，运行测试！** 🚀
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