科技纪年/Tech Craft Chronicles

3X-UI 把复杂的 Xray/Hysteria2 配置变成可视化管理，Xray 负责灵活路由，Hysteria2 擅长 QUIC/UDP，Python 则像一个勤快的小保安，帮你盯着节点是否在线。软件免费开源，但 VPS 和带宽可不是凭空长出来的；好处是跨平台、可控、方便，缺点只是链式代理一多，网络就开始像家庭群聊一样复杂。 3X-UI turns complex Xray and Hysteria2 management into a visual workflow. Xray provides flexible routing, Hysteria2 brings QUIC/UDP performance, and Python acts like a tiny security guard monitoring node health. The setup is flexible and controllable—just remember that too many proxy hops can make networking as complicated as a family group chat. 工欲善其事，必先利其器。想要搭建一个完全掌控在自己手中的远程网络实验环境，其实并没有想象中那么玄乎。今天我们就动手搞定这套极简且高可用的方案！ A bad workman blames his tools, but a great nerd gets the best ones. Building your own fully controlled remote network lab isn't some black magic only wizards can do. Let’s roll up our sleeves and build this dead-simple, rock-solid setup together! Step 1: 准备 Linux VPS / Prepare a Linux VPS 搭建前需准备： 一台 Linux VPS SSH 登录权限 root 或 sudo 权限 一个可用端口 服务器防火墙允许对应 TCP/UDP 流量 免责声明与提示 ：VPS 本身通常不是免费资源。如果要求“完全不花钱”，最现实的路线是使用...

免费 AI 的真正爽点，不是幻想“宇宙级模型永远不限量”，而是 Puter.js 让你少操心 API Key，Hermes Agent 帮你真正干活，Python 负责整理数据，g4f 和免费模型则像备用充电宝。优点是便宜、灵活、跨平台；缺点只是偶尔模型会闹脾气——毕竟免费 AI 也需要喘口气。 The real magic of free AI is not an imaginary bottomless buffet of premium models. Puter.js removes much of the API-key hassle, Hermes Agent actually performs tasks, Python handles the data, and free providers keep costs near zero. It is flexible, cross-platform, and friendly to beginners—although free AI occasionally needs a coffee break too. 1. 一个真正能用的例子/One Practical Example 做一个免费的“AI 视频资料分析器”：输入视频资料文件，Python 自动整理文本，Puter.js 负责 AI 分析，Hermes Agent 自动执行复杂任务，g4f 作为本地 OpenAI-compatible 备用通道。此所谓一举而多得。 Python → 读取/清洗资料 → Puter.js → AI分析                          ↓                    Hermes Agent → 自动执行任务    ...

  别再给云端 AI 交“窝心税”啦！这次咱们直接“白嫖”到底：要么用 Ollama 在本地把模型的“安全紧箍咒”一剪子绞掉，不联网也能放飞自我；要么用 Puter.js 前端白嫖高级模型，连 API Key 都省了！唯一的小缺点，就是本地部署太吃电脑内存（如果显卡太菜，AI 回话比树懒还慢），公益接口有时还像开盲盒一样看运气。总之，云端白嫖，本地越狱，拿捏！ Stop paying the “AI tax”! Go absolute free: either use Ollama to snip the AI’s safety filter for offline creative freedom, or utilize Puter.js for zero-key frontend calls. The only catch? Local setups eat VRAM for breakfast (slow GPU makes AI reply like a sloth), and public proxies are like blind boxes. Anyway, cheat the cloud, jailbreak the local—pure joy! 一个案例，让云端和本地同时为你打工 Most people think using AI means choosing either cloud or local . That’s like believing you can only date either the pretty one or the smart one. Why not let both cooperate? 很多人以为 AI 只能二选一：云端或者本地。其实这就像谈恋爱，以为颜值和智商只能选一个。成年人当然是——两个都要。 真正舒服的方案，是搭建一个“双保险 AI 助手”。日常聊天、写代码、翻译、总结等普通任务，直接交给云端；而涉及隐私、离线环境，或者你希望完全在本机处理的内容，则交给本地模型。整个流程既方便又灵活，体验远比单一路线顺滑。 The better solution is a hybrid workflow. Use cloud AI for everyday tasks like coding, writing...

  仨人组团给你AI请了监工、保镖、还包了自助餐，偶尔装环境会闹点小脾气爱报错，但从此写代码不翻车、不泄密、不花钱，普通人也能一键当老板。 Babysitter, bodyguard, and free buffet for your AI coder. Setup can be a bit grumpy, but it keeps code clean, secrets safe, and wallet at zero – even newbies ship like a pro. 很多人以为，AI写代码最大的瓶颈是模型不够聪明。其实恰恰相反，真正拖后腿的，往往是没有流程、没有隔离、没有安全边界。就像谈恋爱，再优秀的人，如果第一次见面就把银行卡密码告诉对方，最后哭的八成还是自己。 Most people think AI coding is limited by model intelligence. Ironically, the bigger problem is the lack of workflow, isolation, and security. It’s like dating—no matter how charming you are, handing over your bank PIN on the first date rarely ends well. 这套方案最大的魅力，就是把三个官方免费工具组合起来：Claude Code Sandbox负责安全隔离，Superpowers负责工程化流程，而GitHub Models（本文案例基于其可用时期）负责免费模型推理，最终用Python自动生成Markdown日报。整个过程几乎零成本，而且符合现代AI开发流程。需要注意的是，GitHub 已宣布 GitHub Models 将于2026年7月底退役，因此该案例更适合作为工程化思路参考。  The beauty of this stack is combining three official tools: Claude Code Sandbox for isolation, Superpowers for structured engineering, and GitHub Models (available when th...