This module implements a post-training mechanism that allows a language model to explore various reasoning branches (chain-of-thoughts) using a Monte Carlo Tree Search (MCTS) framework. It selects the branch with the best answer using a cosine similarity evaluator that compares the candidate answer to a known correct answer.