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}</script><meta name="generator" content="Hexo 8.1.2"></head><body><div class="page" id="body-wrap"><header class="not-top-img" id="page-header"><nav id="nav"><span id="blog-info"><a class="nav-site-title" href="/"><span class="site-name">徇的小站</span></a></span><div id="menus"></div></nav><h1 class="title-seo">徇的小站</h1></header><main class="layout" id="content-inner"><div class="recent-posts nc" id="recent-posts"><div class="recent-post-items"><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2026/AI%E7%B3%BB%E7%BB%9F%E7%9A%84%E6%B2%99%E7%9B%92%E6%89%A7%E8%A1%8C%E7%8E%AF%E5%A2%83%E8%AE%BE%E8%AE%A1%E6%80%9D%E8%B7%AF.html" title="AI 系统的沙盒执行环境设计思路">AI 系统的沙盒执行环境设计思路</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2026-05-23T04:00:00.000Z" title="发表于 2026-05-23 12:00:00">2026-05-23</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/AI%E4%B8%8E%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/">AI与机器学习</a><i class="fas fa-angle-right article-meta-link"></i><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/AI%E4%B8%8E%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%AE%89%E5%85%A8/">安全</a></span></div><div class="content">背景 在 AI 应用中，LLM 经常需要执行代码——运行 Shell 脚本、读写文件、安装依赖。但 LLM 的输出本质不可信：它可能幻觉出危险命令，也可能在 prompt injection 下被诱导执行恶意代码。 沙盒执行环境因此成为 AI 系统的基础设施。本文从架构设计的角度，拆解一套可落地的沙盒方案。 分层设计：传输与隔离解耦 沙盒有两个可以独立变化的关注点： 关注点一：传输方式——命令怎么发到执行环境？ 开发调试时直接在本地起进程，延迟低 生产环境通过 SSH 发到隔离容器，宿主机零风险 关注点二：隔离级别——用什么力度限制进程？ 轻量级：namespace + chroot + capability drop，适用于开发环境与内部信任任务 严格级：轻量级基础上叠加 seccomp + cgroup（内存/CPU 限制）+ 独立 network namespace + 禁用 /proc，适用于不可信的外部输入 关键是这两个关注点互不耦合——传输方式和隔离级别各写一份实现，按需组合使用，不用为每种"传输+隔离"的组合写一套独立的代码。 flowc...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2026/Chrome%E7%BF%BB%E8%AF%91%E5%BC%BA%E5%88%B6%E4%BB%A3%E7%90%86%E6%96%B9%E6%A1%88.html" title="Chrome 翻译强制代理方案">Chrome 翻译强制代理方案</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2026-05-22T16:19:31.000Z" title="发表于 2026-05-23 00:19:31">2026-05-23</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/">基础设施</a><i class="fas fa-angle-right article-meta-link"></i><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/%E7%BD%91%E7%BB%9C/">网络</a></span></div><div class="content">背景 Chrome 浏览器的内置翻译功能需要直连 Google 服务。只有在开启 Clash 的系统代理或 TUN 模式（全局代理）时，翻译功能才能正常工作。 但我的日常习惯是不开系统代理或 TUN 模式，避免影响其他软件的网络行为。浏览器流量通过 ZeroOmega 插件经 SOCKS5 代理转发到 Clash。 问题在于：ZeroOmega 只能代理网页内容请求，Chrome 内置的翻译请求不经过插件，因此无法使用翻译功能。 解决方案参考：SwitchyOmega/issues/264 原理 核心思路分两步： hosts 劫持：将 Google 翻译域名指向本地回环地址，让翻译请求发往本机 Clash 隧道转发：Clash 监听本地对应端口，将收到的流量通过代理转发到真正的目标服务器 基础方案 步骤 1：修改 hosts 12127.0.0.1 translate.google.com127.0.0.1 translate.googleapis.com 步骤 2：配置 Clash 隧道 在 Clash 配置文件中添加： 12tunnels: - tcp,127....</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2026/%E9%80%9A%E8%BF%87%E4%BB%A3%E7%A0%81%E5%AF%B9%E6%8E%A5ConvertX.html" title="通过代码对接ConvertX">通过代码对接ConvertX</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2026-02-08T12:39:06.000Z" title="发表于 2026-02-08 20:39:06">2026-02-08</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%B7%A5%E5%85%B7%E4%B8%8E%E6%95%88%E7%8E%87/">工具与效率</a></span></div><div class="content">背景 有一个需求是通过代码对接一个格式转换的开源项目用于格式转换，最后选定了ConvertX这个项目，但是发现没有提供直接可用的API接口，只有WEB端的接口，最后通过分析WEB端的接口请求，成功对接了ConvertX的接口。 ConvertX接口分析 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485async ({ jwt, redirect, cookie: { auth, jobId } }) => { if (!ALLOW_UNAUTHENTICATED) { if (FIRST_RUN) { return redirect(`${WEBROOT}/setup`, 302); ...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2026/%E4%BD%99%E5%BC%A6%E7%9B%B8%E4%BC%BC%E5%BA%A6%E7%9A%84%E6%8E%A8%E5%AF%BC%E4%BB%A5%E5%8F%8A%E4%B8%8D%E5%BD%B1%E5%93%8D%E7%9B%B8%E4%BC%BC%E5%BA%A6%E8%AE%A1%E7%AE%97%E7%9A%84%E5%90%91%E9%87%8F%E7%BB%B4%E5%BA%A6%E6%8B%93%E5%B1%95%E6%96%B9%E6%B3%95.html" title="余弦相似度的推导以及不影响相似度计算的向量维度拓展方法">余弦相似度的推导以及不影响相似度计算的向量维度拓展方法</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2026-01-22T08:43:27.000Z" title="发表于 2026-01-22 16:43:27">2026-01-22</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/AI%E4%B8%8E%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/">AI与机器学习</a></span></div><div class="content">背景 以前在存储EMBEDDING模型输出向量的时候，由于不同模型输出的向量维度不同，而向量数据库同一个表只能存储同一维度长度的向量，当时使用的方案是直接在向量后面补0来拓展。 最近在思考这样做为什么不会影响相似度的计算，同时研究了一下余弦相似度计算公式的推导过程。 向量长度 一维向量的长度 对于向量 x=(x)x = (x)x=(x) 它的长度是 ∥x∥=∣x∣\|x\| = |x|∥x∥=∣x∣ 二维向量的长度 对于向量 x=(x1,x2)x = (x_1, x_2)x=(x1,x2) 123456789(x1, x2) * |\ | \x2 | \ ||x|| | \ |____\ x1 它的长度是 ∥x∥=x12+x22\|x\| = \sqrt{x_1^2 + x_2^2}∥x∥=x12+x22 三维向量的长度 对于向量 x=(x1,x2,x3)x = (x_1, x_2, x_3)x=(x1,x2,x3) 它的长度是 ∥x∥=x12+x22+x32\|x\| = \sqrt{x_1^2 + x_2^2 + x_3...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2025/%E5%BC%80%E5%8F%91%E5%B7%A5%E5%85%B7%E6%95%B0%E6%8D%AE%E8%BF%81%E7%A7%BB.html" title="开发工具数据迁移">开发工具数据迁移</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2025-08-14T08:23:26.000Z" title="发表于 2025-08-14 16:23:26">2025-08-14</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%B7%A5%E5%85%B7%E4%B8%8E%E6%95%88%E7%8E%87/">工具与效率</a></span></div><div class="content">背景 最近发现一个问题，我的C盘满了，我用SpaceSniffer检查了一下，发现WSL的数据吃了我将近100G，各种开发环境的包也吃了不少空间，所以打算把这些数据迁移到其他盘，然后通过符号链接的方式来解决这个问题。 迁移WSL wsl的迁移现在已经很简单了，现在可以直接使用move命令来迁移wsl的存储位置 首先看看当前有哪些wsl,记录下要迁移的wsl的名字 1wsl --list 适用于 Linux 的 Windows 子系统分发: Arch (默认值) rancher-desktop-data rancher-desktop 然后开始迁移 12345wsl --manage Arch --move F:\wsl\Archwsl --manage rancher-desktop-data --move F:\wsl\rancher-desktop-datawsl --manage rancher-desktop --move F:\wsl\rancher-desktop 迁移完成后，重新打开wsl，检查数据是否完整 迁移其他开发工具下载的依赖包 比如maven、pip、...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2025/%E4%BD%BF%E7%94%A8Antlr4%E6%9D%A5%E8%A7%A3%E6%9E%90P%E7%A4%BE%E6%B8%B8%E6%88%8F%E7%BE%A4%E6%98%9F-stellaris-%E7%9A%84%E7%A7%91%E6%8A%80%E6%A0%91.html" title="使用Antlr4来解析P社游戏群星[stellaris]的科技树">使用Antlr4来解析P社游戏群星[stellaris]的科技树</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2025-05-18T10:13:06.000Z" title="发表于 2025-05-18 18:13:06">2025-05-18</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%B8%B8%E6%88%8F/">游戏</a></span></div><div class="content">背景 群星更新了4.0，然后新版本的科技树不知道长什么样，科技树mod也坏了，就打算自己修一下，顺便学习一下Antlr4 方案 1. 解析游戏的配置文件 科技树的配置文件在common/technology/目录下 本地化文件在localization/目录下,这次只考虑中文 变量在common/scripted_variables目录下 还有个scripted_trigger在common/scripted_triggers目录下，这次没有用到 每个配置文件的配置项都可以看做是一个对象，对象中有赋值语句和条件计算语句，计划是在grammar中定义整个结构，这样可以在Visitor中读取到每个Property的数据 如 1234567891011121314151617181920212223242526272829303132333435363738394041424344technology_body : technology_body_start ( area | tier | category | icon | modifier ...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2025/%E5%9C%A8%E7%A3%81%E7%9B%98%E4%B8%8A%E5%AE%89%E8%A3%85LiveCD.html" title="在磁盘上安装LiveCD">在磁盘上安装LiveCD</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2025-04-25T12:16:12.000Z" title="发表于 2025-04-25 20:16:12">2025-04-25</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/">基础设施</a><i class="fas fa-angle-right article-meta-link"></i><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/Linux/">Linux</a></span></div><div class="content">安装教程 因为目前切换到了Windows，先简要备注一下大概的步骤，后续有机会再补充详细的步骤 准备一个UEFI启动的分区，格式化为FAT32格式，具体大小看想放多少个镜像，我这边是分了10G,假设分区名称为sda1 将EFI分区挂载到/mnt，然后安装grub，注意需要用removable的方式,这样会把grub所需的模块全部安装到EFI分区 https://wiki.archlinux.org/title/GRUB/Tips_and_tricks#Alternative_installation_methods 12mount /dev/sda1 /mntgrub-install --target=x86_64-efi --bootloader-id=LIVECD --efi-directory=/mnt --boot-directory=/mnt --removable 这样会得到结构的EFI分区 123456789EFI BOOT BOOTX64.EFIgrub fonts locale themes x86_64-efi grubenv 安装...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/Steam%E7%9A%84P2P%E8%81%94%E6%9C%BA%E4%BC%98%E5%8C%96.html" title="Steam的P2P联机优化">Steam的P2P联机优化</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2024-11-22T03:19:50.000Z" title="发表于 2024-11-22 11:19:50">2024-11-22</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/">基础设施</a><i class="fas fa-angle-right article-meta-link"></i><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/%E7%BD%91%E7%BB%9C/">网络</a></span></div><div class="content">背景 最近在玩群星,但是多人联机效果非常差,然后网上调研了一下发现可以用组网工具加速提升联机效果。 使用了一段时间之后发现有时候有效果有时候没有效果,所以研究了一下。 P2P实现的原理 Steam 数据报中继 https://partner.steamgames.com/doc/features/multiplayer/steamdatagramrelay?l=schinese https://partner.steamgames.com/doc/api/ISteamNetworkingSockets#CreateListenSocketP2P https://partner.steamgames.com/doc/api/ISteamNetworkingSockets#ConnectP2P Steam的SDK中提供了可以直接用于P2P的接口,游戏只需要实现接口就实现P2P连接 Steam中的对等网络及共享IP 地址 https://help.steampowered.com/zh/faqs/view/1433-AD20-F11D-B71E 参考这篇文章介绍 使用中继进行对等连接...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/%E5%AE%9E%E7%8E%B0%E4%B8%80%E4%B8%AA%E8%83%BD%E5%A4%9F%E8%87%AA%E5%8A%A8%E5%88%A0%E9%99%A4%E7%9A%84%E4%B8%B4%E6%97%B6%E6%96%87%E4%BB%B6.html" title="实现一个能够自动删除的临时文件">实现一个能够自动删除的临时文件</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2024-08-09T09:38:37.000Z" title="发表于 2024-08-09 17:38:37">2024-08-09</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%90%8E%E7%AB%AF/">后端</a><i class="fas fa-angle-right article-meta-link"></i><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%90%8E%E7%AB%AF/Java/">Java</a></span></div><div class="content">背景 前段时间在弄关于文档转图片然后进行处理的工作,其中由于图片内容会多次读取,所以将其持久化在本地。 但是由于图片是临时文件,所以需要在使用完之后删除。 最初的实现是使用try-with-resource,但是随着流程变得复杂,图片的生命周期变得不可控,所以需要一个更好的解决方案。 思路 利用Cleaner的特性,在文件被GC回收时,进行删除操作。需要注意不要在cleaner中应用this对象,否则会导致内存泄漏。 利用MDC保存当前线程的MDC信息,这样cleaner执行时,用于跟踪上下文的MDC可以保留,使得traceId等信息不会丢失。 实现 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556package com.haizhi.metis.document.parse.common;import java.io.File;import java.io.IOException;import java.lang.re...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/%E8%AE%A9%E8%87%AA%E5%AE%9A%E4%B9%89%E6%B3%A8%E8%A7%A3%E6%94%AF%E6%8C%81%E9%85%8D%E7%BD%AE%E5%B1%9E%E6%80%A7%E6%B3%A8%E5%85%A5.html" title="让自定义注解支持配置属性注入">让自定义注解支持配置属性注入</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time datetime="2024-07-15T01:41:49.000Z" title="发表于 2024-07-15 09:41:49">2024-07-15</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%90%8E%E7%AB%AF/">后端</a><i class="fas fa-angle-right article-meta-link"></i><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%90%8E%E7%AB%AF/Java/">Java</a></span></div><div class="content">背景 在写代码的过程中需要用到一些自定义annotation，但是annotation中的String类型的value需要字符串常量，于是想是否可以将@Value所支持的表达式移植到自定义注解中。 实现 Spring中的具体实现 org.springframework.beans.factory.support.DefaultListableBeanFactory#doResolveDependency 123456789101112131415161718Object value = getAutowireCandidateResolver().getSuggestedValue(descriptor);if (value != null) { if (value instanceof String) { String strVal = resolveEmbeddedValue((String) value); BeanDefinition bd = (beanName != null && cont...</div></div></div></div><nav id="pagination"><div class="pagination"><span class="page-number current">1</span><a class="page-number" href="/page/2/#content-inner">2</a><a class="page-number" href="/page/3/#content-inner">3</a><a class="extend next" rel="next" href="/page/2/#content-inner"><i class="fas fa-chevron-right fa-fw"></i></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info text-center"><div class="avatar-img"><img src="/img/butterfly-icon.png" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info-name">codexvn</div><div 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