Agentbook: Enabling Fine-Grained Editability in Visual Narratives via Page-Centric Agent Coordination

Abstract

Long-horizon visual storytelling with text-to-image diffusion models enables coherent multi-page narratives from a single prompt, yet existing single-pass generation pipelines tightly couple pages within a shared latent trajectory, limiting structured editability. We propose AgentBook, a training-free multi-agent framework that reformulates story generation as a page-centric process governed by an explicit global narrative state encoding character identity, stylistic constraints, and narrative context. By decoupling page synthesis from a monolithic diffusion chain and coordinating story planning, generation, consistency enforcement, and user editing through state-based conditioning, AgentBook enables localized page regeneration and iterative refinement without compromising cross-page coherence. Experimental results demonstrate improvements in story coherence, visual consistency, and edit locality over representative visual storytelling and text-to-image diffusion baselines, establishing a controllable and interactive paradigm for long-form visual narrative generation.