Files
AIclinicalresearch/extraction_service/test_module.py
HaHafeng 98d862dbd4 feat(aia): Complete AIA V2.0 and sync all changes
AIA V2.0 Major Updates:
- Add StreamingService with OpenAI Compatible format (backend/common/streaming)
- Upgrade Chat component V2 with Ant Design X deep integration
- Implement 12 intelligent agents (5 phases: topic/design/review/data/writing)
- Create AgentHub with 100% prototype V11 restoration
- Create ChatWorkspace with fullscreen immersive experience
- Add ThinkingBlock for deep thinking display
- Add useAIStream Hook for stream handling
- Add ConversationList for conversation management

Backend (~1300 lines):
- common/streaming: OpenAI adapter and streaming service
- modules/aia: 12 agents config, conversation service, attachment service
- Unified API routes to /api/v1 (RVW, PKB, AIA modules)
- Update authentication and permission helpers

Frontend (~3500 lines):
- modules/aia: AgentHub + ChatWorkspace + AgentCard components
- shared/Chat: AIStreamChat, ThinkingBlock, useAIStream, useConversations
- Update all modules API endpoints to v1
- Modern design with theme colors (blue/yellow/teal/purple)

Documentation (~2500 lines):
- AIA module status and development guide
- Universal capabilities catalog (11 services)
- Quick reference card
- System overview updates
- All module documentation synchronization

Other Updates:
- DC Tool C: Python operations and frontend components
- IIT Manager: session memory and wechat service
- PKB/RVW/ASL: API route updates
- Docker configs and deployment scripts
- Database migrations and scripts
- Test files and documentation

Tested: AIA streaming verified, authentication working, core features functional
Status: AIA V2.0 completed (85%), all changes synchronized
2026-01-14 19:19:00 +08:00

81 lines
905 B
Python

"""测试dc_executor模块"""
print("测试dc_executor模块导入...")
try:
from services.dc_executor import validate_code, execute_pandas_code
print("✅ 模块导入成功")
# 测试验证功能
print("\n测试validate_code...")
result = validate_code("df['x'] = 1")
print(f"✅ validate_code成功: {result}")
# 测试执行功能
print("\n测试execute_pandas_code...")
test_data = [{"age": 25}, {"age": 65}]
result = execute_pandas_code(test_data, "df['old'] = df['age'] > 60")
print(f"✅ execute_pandas_code成功: success={result['success']}")
if result['success']:
print(f" 结果: {result['result_data']}")
print("\n🎉 所有模块测试通过!")
except Exception as e:
print(f"❌ 测试失败: {e}")
import traceback
traceback.print_exc()