CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society


The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework named role-playing. Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. Our contributions include introducing a novel communicative agent framework, offering a scalable approach for studying the cooperative behaviors and capabilities of multi-agent systems, and open-sourcing our library to support research on communicative agents and beyond.

 Live Demo

Explore CAMEL dataset, see the historic record of agents chat

Make agents chat to each other in real time given your own topic

Chat with a chatbot running a CAMEL model

 Recorded  Demo

Creat a treasure hunt game: Python Programmer & Gamer

Take control of the world: Hacker & AGI

Molecular dynamics simulation: Computational Chemist & Poor PhD Student

CAMEL ChatBot Coding Demo


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