The underlying architecture of CloudBase AI ToolKit adopts a highly modular plug-in system design. Its core component, Meta Controller Proxy (MCP), realizes the flexible expansion of functions through the plug-in mechanism, and developers can enable specific function modules according to project requirements.
The main modules include:
- Environment management: support for multi-environment configuration and switching
- Database Management: Provides CRUD operations and index optimization for cloud databases
- Cloud Functions: Enabling Function Deployment, Triggers and Versioning
- Static web hosting: support for CDN acceleration and custom domain names
The advantage of this plug-in architecture is:
- Reduce the size and complexity of the toolkit
- Support for personalized custom development processes
- Facilitates community contributions and feature iterations
- Reduce unnecessary resource utilization
This answer comes from the articleCloudBase AI ToolKit: a toolset to help developers rapidly build and deploy AI applications to the cloudThe
May not be reproduced without permission:AI productivity tools " CloudBase AI ToolKit's Plug-in System Supports Modular Extension of Environment Management
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