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Basic Information

SkyAGI is a Python package and demo that showcases large language models' emerging ability to simulate believable human behavior by implementing the concept of generative agents. The repository delivers a role-playing experience in which multiple NPCs interact, remember past events, and produce human-like responses. It includes example character configurations drawn from The Big Bang Theory and The Avengers as starting points and supports user-defined characters via JSON configuration files. The project is designed to illustrate how memory, personality, and status can drive autonomous character interactions without constant human direction. It is distributed as an installable package with a command-line entry point named skyagi and requires an OpenAI API key to run.

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App Details

Features
Provides an installable Python package that can be run from the command line with a simple skyagi command. Ships example character JSONs demonstrating personality, memories, age, and current status for ready-made NPCs. Supports custom character configuration files so users can define name, age, personality traits, memory entries, and current status. Demonstrates emergent behaviors such as memory recall, persuasion between agents, and story progression without direct human control. Includes example datasets and a visual screenshot of a demo conversation. Installation options include pip and a make install target. References the Generative Agents research and langchain character examples as conceptual foundation.
Use Cases
SkyAGI helps developers, researchers, and game designers prototype and study believable non-player characters by providing a working implementation of generative agents driven by LLMs. It makes it straightforward to test how memory entries and personality influence dialog and group dynamics, revealing behaviors like remembering past requests, spontaneous persuasion, and autonomous plot advancement. The JSON-based character configs lower the barrier to creating and iterating on many different agent personalities. As a demonstration tool it can inform game writing, NPC scripting, AI-driven storytelling, and research into agent architectures and social simulation. Its CLI and packaged distribution make it easy to reproduce demos and experiment with new characters.

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