Reflexion implements a novel approach to language agent training where agents learn from verbal feedback rather than traditional RL gradients. The framework provides different agent types (ReAct, Chain-of-Thought) and reflexion strategies that allow agents to self-evaluate and refine their reasoning across multiple attempts. The implementation includes benchmarks like HotPotQA for evaluating multi-step reasoning capabilities.