A novel communicative agent framework called role-playing is introduced to enhance autonomous cooperation among communicative agents, providing insights into their cognitive processes by using inception prompting to guide chat agents towards task completion while aligning with human intentions. This approach is showcased as a method to generate conversational data that aids in studying chat agents' behaviors and capabilities, offering a valuable resource for examining conversational language models. The authors have made their library open-source to support further research on communicative agents and related areas, highlighting the framework's potential to evolve chat completions beyond conventional system-user-assistant interactions, possibly enabling multiple AI assistants to collaborate within a single chat instance.