CAMP introduces a multi-model framework that combines local and cloud-based LLMs to enable AI-assisted programming in restrictive environments like Apple's ecosystem.

• Leverages Retrieval-Augmented Generation (RAG) locally for contextual understanding
• Operates efficiently within sandboxed environments where cloud access is limited
• Provides seamless code completion, documentation, and error detection
• Balances performance and privacy through strategic local/cloud processing

This research enables developers in restrictive environments to benefit from AI programming assistance without sacrificing security or performance—making advanced coding tools accessible across more platforms.

Original Paper: Contextual Augmented Multi-Model Programming (CAMP): A Hybrid Local-Cloud Copilot Framework