让游戏与社交平台的虚拟角色用大模型对话并保持记忆同步
LLM-Driven NPCs: Cross-Platform Dialogue System for Games and Social Platforms
- 用大模型驱动角色，跨Unity和Discord平台实时对话
- 通过云数据库存储对话日志，实现跨平台记忆同步
- 为情感建模和长期记忆功能提供可扩展基础
传统游戏中非玩家角色（NPC）受限于静态对话树和单一交互平台。本文提出一个原型系统，使大语言模型（LLM）驱动的NPC能在游戏环境（Unity）和社交平台（Discord）中与玩家进行双向对话。对话记录存储于云端数据库（LeanCloud），实现跨平台记忆同步，保障对话连贯性。初步实验表明跨平台交互在技术上可行，为后续情感建模和持久记忆支持奠定了坚实基础。
原文摘要 · Abstract (English)
NPCs in traditional games are often limited by static dialogue trees and a single platform for interaction. To overcome these constraints, this study presents a prototype system that enables large language model (LLM)-powered NPCs to communicate with players both in the game en vironment (Unity) and on a social platform (Discord). Dialogue logs are stored in a cloud database (LeanCloud), allowing the system to synchronize memory between platforms and keep conversa tions coherent. Our initial experiments show that cross-platform interaction is technically feasible and suggest a solid foundation for future developments such as emotional modeling and persistent memory support.
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