Files
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

cd AIclinicalresearch\tests
run_tests.bat

Linux/Mac用户

cd AIclinicalresearch/tests
chmod +x run_tests.sh
./run_tests.sh

⚠️ 前提条件

必须先启动Python服务

# 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! 🚀