Build a secure local analytics environment
For sensitive industries such as finance/healthcare, AiPy offers complete localized solutions:
- Offline Model Support: Configure local LLMs such as Ollama without the need for internet access throughout the process
- Data Sandbox: All data processing is done in the memory of the user's device and is not transmitted via the cloud
- trace removal: The automatic release of memory variables at the end of a session can be accomplished by the
%resetmanual clearance
Implementation Steps:
- exist
.aipyconfigConfigure the local model API address in - Add at startup
--localParameters ensure network isolation - utilization
ai("分析本地数据库中的患者指标")operate
Special Note: For mega data, it is recommended to test the memory footprint in a virtual environment first.
This answer comes from the articleAiPy: automating the task of running Python code for data analysisThe
May not be reproduced without permission:AI productivity tools " How to overcome privacy risks in local sensitive data processing?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil