CoDi: A Director-Actor Framework for Goal-Driven Interactive Story Generation with LLMs

Abstract

Interactive storytelling offers personalized and engaging narrative experiences but poses significant authoring challenges. Our proposed framework, CoDi, extends the existing director-actor paradigm by enhancing the director agent's control capabilities. Specifically, CoDi uses high-level narrative goals to facilitate adaptive storytelling, with the director agent able to introduce new events, select relevant non-player characters (NPCs), and explicitly describe narrative outcomes. Comparative evaluations have demonstrated CoDi's competitive narrative quality, highlighting its effectiveness in balancing structural control and flexible agent behaviors, thus underscoring its potential as a foundation for scalable interactive storytelling systems. The code is publicly available on Github.