Prompt engineering refers to the process of designing and refining input prompts to guide LLMs in generating desired outputs . The primary function of prompt engineering is to enhance the model's performance by making the instructions clearer, more specific, and aligned with the task at hand. The underlying principle of prompt engineering is based on how LLMs interpret language patterns and context. By manipulating the structure and content of the prompt, the model can be directed toward producing more relevant or specialized outputs . This is achieved by providing the model with a well-defined context, precise formatting instructions, and clear task definitions. In this work, the prompt is divided into several key components: PREFIX, FORMAT_INSTRUCTIONS, QUESTION_PROMPT, SUFFIX, FINAL_ANSWER_ACTION, and REPHRASE_TEMPLATE. Each of these components plays a specific role in shaping the interaction with the model:  PREFIX: Introduces the overall context or background information for the task.