标签：#ha

This is a submission for DEV's Summer Bug Smash: Smash Stories powered by Sentry. ...

This is a submission for Frontend Challenge - Comfort Food Edition, CSS Art . Inspiration I'm from El Salvador, and here comfort food has one name: pupusas . Thick corn tortillas stuffed with cheese, beans and chicharrón, served with curtido (pickled cabbage slaw) and tomato salsa. It's our national dish, but more than that — it's the food you eat at a plastic table at night, under one warm light, with the comal hissing somewhere behind you. That last image is what I wanted to capture. Not just the plate: the moment . So the piece has a light switch. Demo Two things to try: "Bañar en salsa" — pours salsa over each pupusa with a staggered cascade. "Apagar la luz" — turns the whole scene into a night pupusería, lit only by a flickering candle (veladora). Journey Everything is CSS: gradients, border-radius , box-shadow and blend modes. No images, no SVG, no libraries. JavaScript is 15 lines — two class toggles. The tablecloth is the flex. The blue-and-white geometric mantel is five bands built entirely with repeating-conic-gradient and repeating-linear-gradient — chained diamonds, sawtooth rows, chevrons. Zero background images. This was the part I rewrote the most until the patterns locked together. The night is one single element. When you turn off the light, I'm not repainting anything. A single overlay div with mix-blend-mode: multiply holds two stacked radial gradients: near-white around the candle (multiplying by white changes nothing — so that IS the light), falling off to deep blue at the edges. The steam even turns moonlit-blue for free, because that's just what multiply does to white pixels. One div, one blend mode, full day/night mood shift. Corn kernels are two offset dot grids. The mazorca's kernels are two radial-gradient grids shifted by half a cell — which is exactly how kernels interlock on a real cob. That half-cell offset is the difference between "corn" and "polka dots". The curtido is seven crossed stripe layers. White and purple cabbage, carrot, c

Project Overview The project is a React-based web application that fetches data from a REST API and displays it in a dynamic dashboard. Users can navigate between pages, search data, and interact with multiple components that rely on asynchronous API calls. While testing the application, I noticed that navigating away from a page during an active API request occasionally caused React warnings and unnecessary memory usage. This issue affected the application's stability and could lead to performance degradation over time. The problem was caused by an asynchronous operation continuing even after the component had been unmounted. For example, an API request initiated inside useEffect would still complete after the user navigated away, attempting to update the component's state. React would warn that a state update was attempted on an unmounted component. Before useEffect(() => { fetch("/api/users") .then((res) => res.json()) .then((data) => setUsers(data)); }, []); If the component unmounted before the request finished, the callback still attempted to update the state. After I solved the issue by using the AbortController API to cancel the request during cleanup. useEffect(() => { const controller = new AbortController(); fetch("/api/users", { signal: controller.signal, }) .then((res) => res.json()) .then((data) => setUsers(data)) .catch((err) => { if (err.name !== "AbortError") { console.error(err); } }); return () => controller.abort(); }, []); This ensures that pending requests are cancelled when the component unmounts, preventing unnecessary state updates and avoiding memory leaks. Code Prince3963 (Patel Prince) / Repositories · GitHub Prince3963 has 48 repositories available. Follow their code on GitHub. github.com My Improvements This fix focused on improving both performance and application reliability. What I improved Prevented memory leaks caused by unfinished asynchronous requests. Added proper cleanup logic inside useEffect. Eliminated React warnings about u

AI Agent 市场设计:让 Agent 像 App 一样被交易与编排 App Store 把「软件」变成了可被一键购买、安装、评分的商品,AI 时代对应的实体是「Agent」。一个 Agent = 一段可被复用的提示词 + 工具集 + 知识库 + 模型路由配置。本文讲清楚一个 Agent 市场需要哪些核心机制,以及 IHUI-AI 的实现路径。 一、Agent 市场的产品定义 什么是「可上架的 Agent」 不是所有对话 prompt 都能成为商品。一个可上架的 Agent 必须满足: 可独立运行 :用户购买后能立刻用,不需要再写代码。 可复用 :不同用户用同一个 Agent 都能得到稳定结果。 可定价 :有明确的使用边界(次数 / 时长 / 调用规模)。 可评估 :有客观的质量指标(成功率 / 满意度 / 失败率)。 Agent 定义格式 IHUI-AI 用一份 schema 描述可上架的 Agent: const MarketplaceAgentSchema = z . object ({ id : z . string (). uuid (), name : z . string (), description : " z.string(), " // 核心能力 systemPrompt : z . string (), tools : z . array ( z . string ()), // 引用工具/MCP server knowledgeBases : z . array ( z . string ()), // 绑定 RAG 知识库 modelRouting : z . object ({ default : z . string (), // 默认模型 fallback : z . string (). optional (), // 降级模型 }), // 定价 pricing : z . object ({ model : z . enum ([ " free " , " subscription " , " per_call " , " revenue_share " ]), price : z . number (), currency : z . string (). default ( " CNY " ), trialQuota : z . number (). default ( 0 ), }), // 评估 metrics : z . object ({ successRate : z . number (), avgLatencyMs : z . number (), rating : z . number (). min ( 0 ). max ( 5 ), usageCount : z . number (), }), }); 二、四种定价模型 模型 适用 优点 缺点 免费(Free) 引流、品牌 Agent 易扩散 无直接收入 订阅(Subscription) 高频工具型 Agent 收入稳定 流失需运营 按调用计费(Per Call) 低频高价值 Agent 与成本对齐 用户预算焦虑 分成(Revenue Share) 内容生成型 Agent 创作者激励 结算复杂 IHUI-AI 默认采用 订阅 + 按调用混合 :基础功能订阅包月,超出额度按调用计费,创作者拿 70% 分成。 三、Agent 质量评估:四维评分 简单的「5 星好评」不够,因为容易被刷分。IHUI 用四维加权: 任务成功率(40%) :Agent 完成用户原始任务的比率,由 LLM-as-Judge 自动评估。 用户评分(25%) :真实用户打分,过滤异常分布(全是 5 星或 1 星)。 响应延迟(15%) :首 token 时延 + 总时长,归一化到 [0,1]。 稳定性(20%) :错误率 + 重试率,错误越少分越高。 def agent_score ( metrics ) -> float : return ( 0.40 * min ( metrics . success_rate , 1.0 ) + 0.25 * metrics . user_rating / 5 + 0.15 * ( 1 - min ( metrics . p95_latency / 30_000 , 1 )) + 0.20 * ( 1 - min ( metrics . error_rate / 0.1 , 1 )) ) 这个分数实时更新,作为市场搜索排序的依据。 四、Agent 编排:从单个 Agent 到 Agent 工作流 单个 Agent 的能力有上限。Agent 市场的真正价值在于「让用户像搭积木一样编排多个 Agent」。