CAMEL is an open-source framework designed to study the scaling laws of AI agents by simulating large-scale multi-agent systems. It provides tools and resources for researchers to experiment with different agent types, tasks, and environments. The framework emphasizes evolvability, scalability, and statefulness, using code as prompts for agent behavior. CAMEL supports various applications, including data generation, task automation, and world simulation, with extensive documentation and community support. The project encourages contributions and offers synthetic datasets and cookbooks for practical implementation, fostering advancements in multi-agent systems research.