Immediate engineering is an iterative process that always requires intensive guide efforts to formulate appropriate directions for successfully directing massive language fashions (LLMs) in particular duties. Incorporating few-shot examples is a crucial and efficacious method to offer LLMs with exact and tangible directions, resulting in improved LLM efficiency. Nonetheless, figuring out probably the most informative demonstrations for LLMs is labor-intensive, ceaselessly entailing sifting by way of an intensive search house. On this demonstration, we showcase an interactive instrument known as APE (Lively Immediate Tuning) designed for refining prompts by way of human suggestions. Drawing inspiration from lively studying, APE iteratively selects probably the most ambiguous examples for human suggestions, which will probably be reworked into few-shot examples inside the immediate.