Educational content generation using multi-LLM agents

This paper presents a framework for generating educational content using a multi-agent architecture powered by Large Language Models (LLMs). Leveraging the Crew AI framework, the system coordinates multiple autonomous agents, each with specific roles, to produce cohesive educational materials. The agents work collaboratively to generate, detail, direct, and refine content aimed at children under 13, ensuring the inclusion of moral lessons and engaging narratives. This approach enhances the efficiency and effectiveness of content creation, providing a scalable solution for educational material generation.