一年前，我购入了 Meta Ray-ban 眼镜，Meta 对于眼镜本体的开发及 App 更新很快，但由于没有中文支持和开放的SDK 导致对国内用户非常不友好。2025 年 11 月，Meta 终于放出了 Device Access Toolkit 让社区看到了点意思，前两天逛 GitHub 刷到了名为turbometa-rayban-ai 开源项目，项目作者开发了直连中文 App + 百炼 API，实现了几个支持有趣功能（例如中文多模态对话、卡路里检测等）。

路都铺好了：能截流、能传图、能搞 AI 交互。看着 Repo 里的调用代码，似乎加一个服务端的功能不是什么难事？正好前段时间刷短视频，看到某地交警配备了那种“黑科技眼镜”，看一眼车牌就能识别是不是违章车，科技瞬间变成人间烟火。当时我就在想：这玩意儿虽然看起来高大上，但核心逻辑不就是 OCR + 查库 + 规则判断 吗？

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既然有了 turbometa-rayban-ai 解决了样板间问题，我又略懂一些 Agent 架构，能不能用阿里云函数计算 AgentRun功能，把这个原型给“Hack”出来？

“端管云”协同框架

首先我们来梳理一个整体架构图，眼镜本身算力有限，所以我们的策略是：端侧只负责看，云端负责想与处理。 我设计了经典的 “端-管-云” 三层架构：

1.端 (Client)：AI 眼镜 + iOS App。负责“抽帧”和“传图”，做一个无情的传输机器。

2.脑 (Brain)：阿里云函数计算 AgentRun。负责思考“今天是单号还是双号？”、“这车是不是VIP？”。

3.手 (Tools)：阿里云 FC - 函数工具。负责脏活累活，比如查数据库、写日志。