AgentVerse

AgentVerse is a versatile framework designed for the efficient deployment of multi-agent environments powered by large language models (LLMs). It streamlines the creation of custom multi-agent systems for both task-solving and simulations. By providing a set of foundational building blocks and modular components, AgentVerse enables researchers and developers to quickly build and customize interactive environments, freeing them to focus on experimentation rather than implementation details. Key features include configurable agent behaviors, support for tool integration via BMTools, and the ability to create varied environments from classroom scenarios to complex simulations like the Prisoner's Dilemma.

AgentVerse's flexibility allows users to tailor environments by customizing five core rule components: environment, agent, selector, updater, and describer. This modular design accommodates diverse research needs, from academic explorations of emergent behaviors to practical applications such as software design and database management. The framework also provides example cases, showcases various configurations, and supports integration with local models via FastChat and vLLM for users requiring local processing. Its open-source nature encourages community collaboration and contributions from researchers and engineers. AgentVerse is an ideal solution for those exploring the exciting intersection of LLMs and multi-agent interaction.