与「SCRAP」相关的搜索结果

Github上这个AI找工作的仓库火了🔥 我原本以为 AI 求职就是帮你改改简历，结果有人直接把整个找工作流直接搭出来了！ 作者自己就是第一批小白鼠：2025 年底被裁后，用这套东西跑了 69 份定制申请 → 20 次一面 → 最后拿到合同，2026 年 6 月转成 AI Engineer。这个仓库 3 月才创建，现在已经 3.4 万+ Stars。 把自己的 LinkedIn、学历、过去申请记录丢进去，它先建立一份长期职业档案。之后 /scrape 自动找岗位并去重，/rank 按你的技能、经历、地点、语言和职业目标批量打分，真正值得投的再进 /apply。 最爽的是 /apply 不是“给我写一份简历”这么简单。 它会先判断匹配度，再针对 JD 重写 CV 和求职信，然后再拉一个 Reviewer Agent 当招聘经理挑刺，检查关键词、经历真实性、公司针对性，修改完还会编译成 PDF、检查 ATS 能不能正常读取。 而且这套系统会记账：投过什么、面了几轮、被拒还是拿 Offer，都能留下来。后面面试时，它直接拿当时那份 JD + 你真正投出去的 CV + 求职信 + 前几轮反馈给你准备，而不是重新瞎猜。 甚至还能读 Gmail 找面试邀请、拒信和 Offer，再同步到自己的求职 Pipeline。 这才是我觉得这个项目最聪明的地方：它不是拿 AI 帮你写求职材料，而是把“找工作”本身做成了一套 Agent 工作流。 GitHub：

En Café Cursor y hoy estuve armando un scraper de Reddit para ver posts en la terminal. Qué problema busco resolver? En mi caso, me gusta comentar en reddit, pero no me gusta buscar temas para hablar en la UI, lo siento como un desperdicio de tiempo. Post sigue abajo ⬇️

该框架为AI代理提供更强大的网络层 • Scrapling将抓取、爬取、提取和MCP访问合为一体 • 适应网站变化，同时保持代理工作流更快更可靠 仓库：

SHE PULLS IN $46,000 A MONTH FROM 9-SECOND STRETCH CLIPS IN PINK SHORTS Three fitness brands dropped their real ambassadors this quarter and signed her instead She's not real. She's never been real A 21-year-old in Tokyo runs everything from a kitchen table with one monitor and a cloud GPU subscription. No gym membership. No camera. No talent agent The blonde hair catches the window light correctly because every clip renders from the same locked HDRI environment map same room, same morning sun, same angle. The way the blue crop top rides up during the overhead stretch, the exact tension in the pink fabric, the muscle definition that shifts frame by frame all controlled by a motion reference library he spent one weekend building and hasn't touched since An automated pipeline scrapes trending fitness audio, maps her movement to the beat, color-grades to match the clean bright aesthetic brands love, and pushes across 42 accounts before he finishes his coffee No shoots. No edits. No content calls. No cancellations 33 million views a week. Two supplement affiliate links. One premium subscription tier. Three brand deals closed entirely over DM Overhead: $55 a month in compute Real fitness creators are spending $3,000 per shoot day to compete with a girl who costs less per month than her own protein powder would He locked one blonde in one bright room ten months ago. Same face. Same shorts. Same stretch. Never changed a thing One character. One window. One pipeline. Revenue that doesn't need a gym

O’KEEFE INVESTIGATES DUPLICATE ABSENTEE BALLOT RETURN ENVELOPES IN DETROIT, MICHIGAN GOES DOOR TO DOOR INTERVIEWING AFFECTED VOTERS "That's illegal right? you couldn't... scrape one of them off?" “They probably sent her two ballots, and she just signed them, I guess.” "Keep them [cameras] pointed from my house... Do you want me to get the dog?"

I was a bricklayer. It was how I paid the bills when I first moved to America. Even the biggest title in bodybuilding, Mr. Olympia, only paid a thousand dollars back then.  It makes me proud that in March, the winner of our Arnold Classic and our Arnold Classic UK took home more than a million dollars. He can focus on bodybuilding. But in our day, that wasn’t an option. Some guys were teachers. Some sold insurance. Franco and I laid bricks. We put an ad in the paper and sold ourselves as European craftsmen. We figured if people heard the accents, they would picture old-world masonry instead of two bodybuilders with a wheelbarrow.  It worked.  The phone rang. And then we had to go out and actually do the job, which was the part nobody could fake. Luckily, Franco knew what he was doing. The work was simple. Mix the mortar. Set the brick. Tap it level. Scrape the edge. Then do it again. And again. Nobody claps for you. There is no crowd, no music, no trophy. There is just the next brick sitting there waiting for you. You can still find some of the walls we built in Venice. That’s where my lesson today comes from. One brick doesn’t look like anything. Ten bricks don’t look like anything. A hundred bricks, you’re starting to see something, but it doesn’t impress anyone. You just keep laying bricks until the job is done. And you know what happens after four or five hours on a wall? You are so damn tired, or you feel so great that you stop measuring. You are not standing back every ten minutes asking how far from finished it is. You are covered in mortar, your hands are raw, you’re schvitzing, and you are happy. The work took the question away from you. That is the part nobody tells you about hard work: It doesn’t just build the wall. It terminates the voice that keeps asking when the wall will be done.

Today, we’re excited to open-source TwiL-LM3, the first formal reasoning model from the webAI Intelligence Lab. At just 3 billion parameters, TwiL-LM3 outperforms OpenAI’s GPT-OSS-120B on 4 of 5 formal reasoning benchmarks while running efficiently on consumer hardware. That’s 40× fewer parameters, 2.6× faster inference, and state-of-the-art performance in the reasoning tasks that power reliable tool calling, code generation, structured outputs, and AI agents. TwiL-LM3 was trained using webAI’s proprietary reasoning pipeline on webAI-owned, verified datasets—not scraped internet data. We believe better reasoning comes from better training pipelines and higher-quality data, not simply larger models. Our approach demonstrates that efficient models can rival—and in many cases surpass—models dozens of times their size. Designed for the edge, TwiL-LM3 runs on hardware people already own—from a Raspberry Pi to an iPhone—bringing advanced reasoning to millions of devices without relying on the cloud. This is our first open-source release from the webAI Intelligence Lab, and it’s only the beginning. Proudly built in Austin, Texas. Article:

Introducing the Firecrawl plugin for Codex. Give Codex access to the most accurate search available (94.7% on SimpleQA) plus tools to scrape, crawl, and interact with any site. Find us on the @OpenAI plugin marketplace today!