The rapid advancement of large language models (LLMs) has unlocked transformative potential for role-playing emotional companion products, enabling systems that support emotional well-being, educational development, and therapeutic applications. However, existing approaches often lack sustained personalization and contextual adaptability, limiting their effectiveness in real-world settings. In this paper, we introduce iPET, an LLM-powered virtual pet agent designed to enhance user engagement through rich, dynamic pet behaviors and interactions tailored to individual preferences. iPET comprises three core components: a dialogue module that instantiates virtual pet agents for emotionally interactive conversations; a memory module that stores and synthesizes records of both agent and user experiences; and a world simulation module that generates diverse, preference-driven pet behaviors guided by high-level reflections. Deployed for over 200 days in a real-world, non-commercial product, iPET has served millions of users – providing emotional support to psychologically distressed individuals and demonstrating its effectiveness in practical applications.