Optimization decision engine for LLM Auto-Optimizer
This crate provides the decision-making logic for optimizing LLM configurations, including A/B testing, Thompson Sampling, statistical significance testing, contextual bandits for reinforcement learning, Pareto optimization, adaptive parameter tuning, drift & anomaly detection, and a comprehensive model registry for all major LLM providers.