Chatbot-based customer support services have significantly advanced with the introduction of large language models (LLMs), enabling enhanced response quality and broader application across industries. However, while these advancements focus on reducing business costs and improving customer satisfaction, limited attention has been given to the experiences of customer service agents, who are critical to the service ecosystem. A major challenge faced by agents is the stress caused by unnecessary emotional exhaustion from harmful texts, which not only impairs their efficiency but also negatively affects customer satisfaction and business outcomes. In this work, we propose an LLM-powered system designed to enhance the working conditions of customer service agents by addressing emotionally intensive communications. Our proposed system leverages LLMs to transform the tone of customer messages, preserving actionable content while mitigating the emotional impact on human agents. Furthermore, the application is implemented as a Chrome extension, making it highly adaptable and easy to integrate into existing systems. Our method aims to enhance the overall service experience for businesses, customers, and agents.

翻译：随着大语言模型（LLMs）的引入，基于聊天机器人的客户支持服务取得了显著进展，提升了响应质量并拓宽了跨行业应用范围。然而，尽管这些进展聚焦于降低企业成本与提高客户满意度，却鲜少关注客户服务专员（他们在服务生态系统中至关重要）的体验。专员面临的主要挑战源自有害文本引发的非必要情绪耗竭所导致的压力，这不仅损害其工作效率，还对客户满意度与业务成果产生负面影响。本研究提出一个基于大语言模型的系统，旨在通过处理情绪密集型沟通来改善客户服务专员的工作环境。该系统利用大语言模型转换客户消息的语气，在保留可操作内容的同时减轻对人类专员的情绪冲击。此外，该应用以Chrome扩展程序形式实现，具备高度适应性且易于集成至现有系统。本方法致力于提升企业、客户与专员三方的整体服务体验。