Jev Based Adaptive Thinking for LLMs

Explain Like I'm Normal

This project introduces a method to trigger 'thinking blocks' in LLMs only when token entropy is high, rather than forcing a fixed reasoning chain. It uses a gate to decide when to branch out into parallel tree-based conversations to resolve uncertainty. This allows local models to scale compute dynamically based on the complexity of the prompt.