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AIclinicalresearch/tests/QUICKSTART_快速开始.md
HaHafeng 96290d2f76 feat(aia): Implement Protocol Agent MVP with reusable Agent framework
Sprint 1-3 Completed (Backend + Frontend):

Backend (Sprint 1-2):
- Implement 5-layer Agent framework (Query->Planner->Executor->Tools->Reflection)
- Create agent_schema with 6 tables (agent_definitions, stages, prompts, sessions, traces, reflexion_rules)
- Create protocol_schema with 2 tables (protocol_contexts, protocol_generations)
- Implement Protocol Agent core services (Orchestrator, ContextService, PromptBuilder)
- Integrate LLM service adapter (DeepSeek/Qwen/GPT-5/Claude)
- 6 API endpoints with full authentication
- 10/10 API tests passed

Frontend (Sprint 3):
- Add Protocol Agent entry in AgentHub (indigo theme card)
- Implement ProtocolAgentPage with 3-column layout
- Collapsible sidebar (Gemini style, 48px <-> 280px)
- StatePanel with 5 stage cards (scientific_question, pico, study_design, sample_size, endpoints)
- ChatArea with sync button and action cards integration
- 100% prototype design restoration (608 lines CSS)
- Detailed endpoints structure: baseline, exposure, outcomes, confounders

Features:
- 5-stage dialogue flow for research protocol design
- Conversation-driven interaction with sync-to-protocol button
- Real-time context state management
- One-click protocol generation button (UI ready, backend pending)

Database:
- agent_schema: 6 tables for reusable Agent framework
- protocol_schema: 2 tables for Protocol Agent
- Seed data: 1 agent + 5 stages + 9 prompts + 4 reflexion rules

Code Stats:
- Backend: 13 files, 4338 lines
- Frontend: 14 files, 2071 lines
- Total: 27 files, 6409 lines

Status: MVP core functionality completed, pending frontend-backend integration testing

Next: Sprint 4 - One-click protocol generation + Word export
2026-01-24 17:29:24 +08:00

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# 🚀 快速开始 - 1分钟运行测试
## Windows用户
### 方法1双击运行最简单
1. 双击 `run_tests.bat`
2. 等待测试完成
### 方法2命令行
```cmd
cd AIclinicalresearch\tests
run_tests.bat
```
---
## Linux/Mac用户
```bash
cd AIclinicalresearch/tests
chmod +x run_tests.sh
./run_tests.sh
```
---
## ⚠️ 前提条件
**必须先启动Python服务**
```bash
# 打开新终端
cd AIclinicalresearch/extraction_service
python main.py
```
看到这行表示启动成功:
```
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:8001
```
---
## 📊 预期结果
**全部通过**
```
总测试数: 18
✅ 通过: 18
❌ 失败: 0
通过率: 100.0%
🎉 所有测试通过!
```
⚠️ **部分失败**
- 查看红色错误信息
- 检查失败的具体测试
- 查看Python服务日志
---
## 🎯 测试内容
- ✅ 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
- ✅ MICE多重插补单列、多列
- ✅ 边界情况100%缺失、0%缺失、特殊字符)
- ✅ 各种数据类型(数值、分类、混合)
- ✅ 性能测试1000行数据
---
## 💡 提示
- **第一次运行**会自动安装依赖pandas, numpy, requests
- **测试时间**约 45-60 秒
- **测试数据**自动生成,无需手动准备
- **颜色输出**:绿色=通过,红色=失败,黄色=警告
---
## 🆘 遇到问题?
### 问题1无法连接到服务
**解决**确保Python服务在运行`python main.py`
### 问题2依赖安装失败
**解决**:手动安装 `pip install pandas numpy requests`
### 问题3测试失败
**解决**:查看错误信息,检查代码逻辑
---
**准备好了吗?启动服务,运行测试!** 🚀