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GitHub热门项目 | 猫抓 浏览器资源嗅探扩展 / cat-catch Browser Resource Sniffing Extension | Stars: 20,754 | 214 stars this week | 语言: JavaScript

GitHub热门项目 | Voice-to-text dictation app with local (Nvidia Parakeet/Whisper) and cloud models (BYOK). Privacy-first and available cross-platform. | Stars: 4,671 | 190 stars this week | 语言: JavaScript

GitHub热门项目 | Self-hosted AI coding assistant | Stars: 33,768 | 13 stars today | 语言: Rust

GitHub热门项目 | Self-hosted deployment platform | Stars: 4,014 | 1,719 stars today | 语言: TypeScript

GitHub热门项目 | Free, open-source web app for learning about ontologies and Microsoft Fabric IQ. Explore a catalogue of pre-built ontologies, design your own visually, export as RDF/XML, and share interactive diagrams. Zero backend, fully static. | Stars: 1,549 | 487 stars today | 语言: TypeScript

GitHub热门项目 | A cross-platform, customizable science fiction terminal emulator with advanced monitoring & touchscreen support. | Stars: 44,986 | 8 stars today | 语言: JavaScript

GitHub热门项目 | 一个人人都能部署的基于 js 的弹幕 API 服务器，支持爱优腾芒哔咪人韩巴狐乐西埋帆弹幕直接获取，兼容弹弹play的搜索、详情查询和弹幕获取接口规范，并提供日志记录，支持vercel/netlify/edgeone/cloudflare/docker/hf等部署方式，不用提前下载弹幕，没有nas或小鸡也能一键部署。 | Stars: 2,789 | 13 stars today | 语言: JavaScript

GitHub热门项目 | MCP server for interfacing with Godot game engine. Provides tools for launching the editor, running projects, and capturing debug output. | Stars: 4,810 | 25 stars today | 语言: JavaScript

GitHub热门项目 | 🚀 The fast, Pythonic way to build MCP servers and clients. | Stars: 26,378 | 77 stars today | 语言: Python

InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants' own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul. By Artenisa Chatziou

Introduction A callback function is one of the most important concepts in JavaScript. It allows one function to execute another function after completing a task. Callback functions are widely used in JavaScript for handling asynchronous operations such as API requests, file reading, event handling, and timers. What is a Callback Function? A callback function is a function that is passed as an argument to another function and is executed later. In simple words: A callback is a function that is called after another function finishes its work. Syntax function greeting () { console . log ( " Good Morning! " ); } function welcome ( callback ) { console . log ( " Welcome! " ); callback (); } welcome ( greeting ); Output Welcome! Good Morning! Explanation greeting() is the callback function. welcome() accepts a function as a parameter. callback() executes the greeting function after printing "Welcome!". Real-Life Example Imagine you order food at a restaurant. You place the order. The chef prepares the food. After the food is ready, the waiter serves it. Here, serving the food happens only after preparation is complete. This is exactly how callback functions work. Example 1: Email Sending function emailSent () { console . log ( " Email Sent Successfully! " ); } function sendEmail ( callback ) { console . log ( " Sending Email... " ); callback (); } sendEmail ( emailSent ); Output Sending Email... Email Sent Successfully! Example 2: Download File function downloadComplete () { console . log ( " Download Complete! " ); } function downloadFile ( callback ) { console . log ( " Downloading File... " ); callback (); } downloadFile ( downloadComplete ); Output Downloading File... Download Complete! Why Do We Use Callback Functions? Callback functions are useful because they: Execute code only after another task finishes. Improve code reusability. Handle asynchronous operations. Make event handling easier. Help avoid repeating code. Where Are Callback Functions Used? Some common u

Why we built Veridexa Many document analysis workflows still rely primarily on OCR OCR is useful for extracting text, but it cannot answer one important question: Does this document show signs of fraud or manipulation? That question led us to build Veridexa. The problem Organizations receive thousands of digital documents every day: Passports National IDs Academic certificates Bank statements Employment documents Invoices Reading the text is only one part of the process. The difficult part is detecting manipulation, inconsistencies, forgery, or suspicious evidence before making a decision. Our approach Instead of relying on OCR alone, Veridexa combines multiple evidence sources into a single fraud assessment. The platform analyzes: OCR extraction Metadata Image forensics Security features Document structure Cross-evidence consistency The result is an explainable decision instead of a simple confidence score. Explainable decisions Every analysis ends with one of three outcomes: ACCEPT MANUAL REVIEW REJECT Each decision is accompanied by supporting evidence so reviewers understand why the system reached that conclusion. Public benchmark We also believe AI systems should be transparent. For that reason Veridexa publishes a public benchmark together with methodology and performance reporting instead of asking users to trust marketing claims. API-first Try the public demo, explore the benchmark, or integrate the API. Feedback from developers and security professionals is always welcome. https://veridexa.io Developers can integrate Veridexa into their own applications using our API while organizations can use the web platform without writing code. We'd love your feedback We're continuing to improve the platform and would genuinely appreciate feedback from the developer community. Website: https://veridexa.io

It's Monday morning. You open your laptop. Coffee sits beside you. LinkedIn is open in one tab. A job portal is open in another. Your inbox is empty. Before lunch, you've already applied for five jobs. Tomorrow, you'll probably do it all again. This is why people say, "Finding a job is a full-time job." But once you're living it, you realize it isn't just a saying—it's a reality. Unlike a regular job, there's no salary, no weekends off, no annual leave, and no guarantee that today's effort will lead to tomorrow's opportunity. More Than Just Clicking "Apply" From the outside, job hunting looks simple. Upload a resume. Click Apply . Repeat. In reality, every application is a small project. The resume is tailored to match the job description. A cover letter is rewritten. LinkedIn is updated. The company is researched. Interview questions are reviewed. Sometimes a portfolio is improved before clicking Submit . What looks like a two-minute application often takes thirty minutes—or more. Multiply that by dozens of applications, and job hunting quickly becomes a full-time commitment. The Numbers Nobody Sees Fifty applications. Ten automated acknowledgements. Three interview invitations. One final-round rejection. And then... The cycle begins again. Many applications never receive a response. Some positions are filled internally. Others are paused, redefined, or quietly removed. From the candidate's perspective, every unanswered application feels the same—another day without clarity. The system doesn't tell you if you were close. It only tells you if you made it. _ Waiting Becomes Part of the Process After clicking Apply , another phase begins. Waiting becomes part of the routine. Refreshing email. Checking LinkedIn. Looking for missed calls. Hoping today's notification finally brings good news. A rejection can be disappointing. But uncertainty is often harder. At least a rejection provides an answer. Uncertainty leaves people creating their own. The Work Doesn't Stop After

Your Contact Form 7 form can work perfectly from a user's perspective and still fail to deliver a lead to your CRM. The visitor fills out the form. The browser shows a success message. The WordPress form appears to have submitted correctly. But when you open Systeme CRM, the contact is nowhere to be found. This is one of the most confusing problems in form-to-CRM integrations because a successful form submission does not necessarily mean a successful API request. The complete workflow has multiple stages: Visitor ↓ Contact Form 7 ↓ WordPress ↓ API Request ↓ Systeme CRM ↓ Contact Record ↓ CRM Automation A failure at any stage can break the workflow. The key to debugging the integration is to stop treating the form submission as a single event and start checking each stage separately. First, separate the two different types of success There are two different questions: Did Contact Form 7 submit the form? This is a WordPress-side question. Did Systeme CRM accept and process the API request? This is an API and CRM-side question. These are not the same thing. A form can successfully collect: Name: John Doe Email: john@example.com Company: Example Inc. while the API request fails because: the endpoint is incorrect authentication is missing the request method is wrong the JSON payload is invalid the CRM expects different field names a required field is missing The first debugging step is therefore to identify exactly where the data flow stops. Step 1: Confirm that Contact Form 7 is collecting the expected data Start at the beginning. Look at the form fields: [text* your-name] [email* your-email] [tel your-phone] [text company] [textarea your-message] The important values are the actual field names: your-name your-email your-phone company your-message A common mistake is to assume that the visible label is the field name. For example: Visible label: Full Name Field name: your-name The integration needs the submitted field value associated with the actual field name. Before