标签：#opensource

A year and a half ago, I wasn't trying to build an AI company. I was building a small social platform called spritex-social — nothing fancy, just a side project a handful of friends were testing with me. No grand plan, no investors, no roadmap beyond "let's see if people like this." At some point, users started asking the same basic questions over and over: how do I change my profile, where's this setting, how does that feature work. Instead of writing endless documentation, I thought — why not just let AI answer this? So I wired up Google's Gemini API through Google AI Studio, built a small Retrieval-Augmented Generation (RAG) system, and gave it context about the platform. It was supposed to be a support chatbot. Nothing more. That's not how it went. I found myself spending more time improving the chatbot than improving the actual social app. Every small upgrade made me ask another question: could it remember conversations? Could it use tools? Could it search the web? Could it do things instead of just answering questions? The more I asked, the less interested I became in the social platform I was supposed to be building. Eventually I had to admit it to myself: I wasn't building spritex-social anymore. I was building something else entirely. So I stopped. Not because the project failed — because my attention had already moved somewhere else, and I finally stopped pretending otherwise. That "somewhere else" became RexiO — a Bangla-first AI platform I've been building solo ever since: my own orchestration layer, an intent classifier, 30+ tools, model routing across providers, and eventually our own fine-tuned models trained from scratch on borrowed Colab GPUs. RexiO went public on July 10, 2026. This chatbot pivot is just one chapter of a much longer story — one that actually starts on a Nokia button phone, ২ টাকা data packs, and a ৳20 freelance job that became my first line of code in production. I wrote the whole thing down, unfiltered — the rewrites, the 12-hour

Here we're going to cover the installation steps of Browsers in Linux - specifically, Debian GNU/Linux . We're covering the procedural steps for this in Debian Testing (Forkey), which is already beginning the gleanings of what will become Debian 14. At the time of writing,the current kernel version is 7.0.13+deb14-amd64. Daily drivers will likely be along the lines of Vivaldi, Firefox, Lagrange, and Brave Browser, and in no particular order. Any others will be mostly for particular reasons like, testing, curiosity, Etc., but some specialized products like the Tor browser, which focus on privacy are also covered. This list is by no means complete, but there's a bunch of them we cover, so let's jump right in! I can haz #Cheezburgerz? 🍔 🍟 Well, let's see... First up is the first rate and fully featured Vivaldi, built on top of the open source Chromium, as are so many others in this list. Vivaldi Manual setup of the Vivaldi Linux repos - According to their website, "you no longer need to do this. After downloading a Linux package and installing it our Linux update repositories will be configured automatically for you to receive updates." That's awfully nice, so visit the download page above and get the .deb package: ~# mkdir -pv /usr/local/packages/vivaldi ; cd /usr/local/packages/vivaldi ~# wget https://downloads.vivaldi.com/stable/vivaldi-stable_8.1.4087.48-1_amd64.deb ~# apt install ./vivaldi * .deb That's it! You're ready to go now. Next up... Firefox ~# apt update && apt install firefox-esr There's none of this messing about anymore with softforks and trying to remember their names...'IceCat?', 'IceWeasel?'. The Trademark issues over branding have been resolved (and that's a good thing). The one thing you might want to look into is SeaMonkey , which combines the Browser with an email client (like Thunderbird), an RSS Reader, IRC client, and a few other goodies. Brave Browser ~# apt install curl ~# curl -fsSLo /usr/share/keyrings/brave-browser-archive-keyring.gpg ht

GitHub热门项目 | Delightful JavaScript Testing. | Stars: 45,535 | 81 stars today | 语言: TypeScript

GitHub热门项目 | The official Python library for the OpenAI API | Stars: 31,211 | 92 stars today | 语言: Python

GitHub热门项目 | CLI tool for configuring and monitoring Claude Code | Stars: 28,654 | 104 stars today | 语言: Python

GitHub热门项目 | Asio C++ Library | Stars: 6,035 | 87 stars today | 语言: C++

GitHub热门项目 | A modern, C++-native, test framework for unit-tests, TDD and BDD - using C++14, C++17 and later (C++11 support is in v2.x branch, and C++03 on the Catch1.x branch) | Stars: 20,570 | 69 stars today | 语言: C++

GitHub热门项目 | Skills for Real Engineers. Straight from my .claude directory. | Stars: 164,017 | 1,728 stars today | 语言: Shell

GitHub热门项目 | A YAML parser and emitter in C++ | Stars: 6,050 | 65 stars today | 语言: C++

GitHub热门项目 | Abseil Common Libraries (C++) | Stars: 17,472 | 3 stars today | 语言: C++

The problem every self-hoster hits You built something. A local API. A Minecraft world for your friends. A self-hosted dashboard. An ERP running on the office machine. It works great — on your LAN. The moment you want someone outside to reach it, the fun begins: Port forwarding? Good luck if you're behind CGNAT, a corporate firewall, or an ISP that doesn't give you a public IP. VPN? Now every person who wants access has to install a client, join a network, and stay connected. Overkill for "let me show you this one page." Cloud deploy? Now you're maintaining two environments, paying for a VPS you didn't need, and shipping data somewhere it doesn't have to live. What most people actually want is simpler: take this one local port, give it a public address, done. That's exactly what FRP does. What FRP is FRP (Fast Reverse Proxy) is an open-source tool by fatedier that exposes a local service behind a NAT or firewall to the public internet. It's battle-tested, written in Go, and has been the go-to answer in self-hosting communities for years. The model is clean — two pieces: frps (the server) — runs on a machine with a public IP (a $5 VPS is plenty). frpc (the client) — runs on your local machine, the one with the service you want to expose. The client opens an outbound tunnel to the server. The server listens on a public port and forwards traffic back through the tunnel. NAT and firewalls don't matter because the connection is initiated from inside . [Visitor] → [frps on public VPS:7000] ⇄ tunnel ⇄ [frpc on your laptop] → [localhost:8080] That's the whole idea. It works for TCP, UDP, HTTP, HTTPS. People run Minecraft servers, remote desktops, internal dashboards, and dev previews through it every day. The catch: config files FRP works great. The friction isn't the protocol — it's the workflow . To run frpc , you write a TOML/INI config file: serverAddr = "203.0.113.10" serverPort = 7000 auth.token = "your-secret-key" [[proxies]] name = "my-web" type = "tcp" localIP = "1

BDE Score™ — Open-Source Multi-Factor Stock Analysis One number. 0-100. Every stock. A composite score combining 5 dimensions: Momentum (30%), Volatility (25%), Volume (20%), Trend (15%), Risk (10%). Coverage : 74 stocks across US (25), Hong Kong (26), and A-Share China (23) markets — all in real-time. Why It's Different Zero signup — REST API works without authentication Multi-market — US, HK and A-Share coverage Transparent scoring — Every factor weight is documented Open source — Full methodology on GitHub Real-time badges — Embed live scores in any README Quick Start curl "https://atlantic-remains-atomic-floor.trycloudflare.com/api/analyze?market=ALL" Links GitHub: https://github.com/hbhqq9/bde-score Live Demo: https://atlantic-remains-atomic-floor.trycloudflare.com/api/snapshot?market=ALL Not financial advice. Technical service for educational purposes. ⭐ Star us on GitHub!

GitHub热门项目 | Visual testing tool for MCP servers | Stars: 10,331 | 13 stars today | 语言: TypeScript

GitHub热门项目 | Automatic quad remeshing tool | Stars: 2,430 | 403 stars today | 语言: C++

You've seen the alert. You've opened the PR. You've read the changelog. Then you realize: your code doesn't even call the vulnerable function. Every week. Hundreds of teams drowning in CVE notifications for packages sitting dormant in their node_modules — dependencies they pulled in years ago, bundled by a transitive library, and never actually executed. Meanwhile, the real vulnerabilities get buried. VigilOps is a free Node.js CLI that fixes this. How VigilOps Works VigilOps does three things: Scans dependencies against OSV.dev — the open vulnerability database used by GitHub, PyPI, and npm Runs static reachability analysis to filter out unreachable vulnerabilities (packages in your tree but never called by your code) Auto-opens a GitHub PR with the fix The result: you get one PR with one real vulnerability. Not a spreadsheet. Not a wall of Slack messages. A fix. Demo Here's a quick scan: npx vigilops scan examples/vigilops-demo-lodash And to see everything including suppressed (unreachable) deps: npx vigilops scan examples/vigilops-demo-express --all The --all flag shows what's in your dependency tree but not actually reachable from your code. That's what the noise looks like — and that's what VigilOps filters out. Why This Is Different Dependabot and Snyk scan your entire lockfile. They report every CVE in every package, regardless of whether your code ever touches the vulnerable surface. This creates alert fatigue that causes teams to eventually... stop reading. VigilOps inverts the model: only surface vulnerabilities in code you actually call. Dependabot: "Your project has 47 vulnerabilities" (but 40 are unreachable noise) VigilOps: "Your project has 1 reachable vulnerability. PR is ready." Quick Start npm install -g vigilops npx vigilops scan . Authenticate with GitHub: https://github.com/Vigilops/vigilops npx vigilops auth That's it. The first run will scan, analyze, and open a PR if there's a fixable reachable vulnerability. What's Included OSV.dev integrati

GitHub热门项目 | YouTube到AcFun和bilibili自动化搬运工具，支持AI翻译、字幕生成、内容审核、智能监控 | Stars: 1,535 | 211 stars today | 语言: Python

Quick confession: this started as "let me stop babysitting my tests and just make them stay green," and it turned into something a lot bigger. I want to be upfront about where I'm actually trying to take it. I built Claude Basecamp, and as of today it's open source. The reconciliation loop (declare "tests always green," it holds that true) is the part you'll notice first, but it's not really the point. The point is I want this to become the operating system for everything you do with Claude Code, one place that knows about every repo, every session, every routine, every connector, every skill, and every mistake it's ever made, instead of all of that living scattered across terminal windows and dead transcripts. Right now it already covers a decent chunk of that: npx claude-basecamp No install, no config. It finds the projects Claude Code already knows about and opens at http://localhost:4747 . Standing checks , the reconciliation loop. "Tests always green," "dependencies current," "the README documents every CLI flag" — say it once, Basecamp keeps it true, dispatches a fix run when it drifts, and only bugs you for the decisions that actually need a human. Reflexes. It goes back through your old transcripts, finds every time you said "no, don't do that," and turns it into a standing memory that every Claude Code session on your machine checks before touching Bash, Write, or Edit. A mistake made once doesn't get to happen a third time. Session Rescue. Resumes the actual dead session, same session ID, full context, when Claude Code dies mid-task, instead of starting over from scratch. A manager for every repo you just talk to: "keep the tests green," "track this goal," "what's the state of this repo?" Plus routines, background runs, an activity feed, stats, GitHub issue and PR hooks, notifications, webhooks, and a one-click catalog for connectors and skills. That's where it is today. What I actually want it to become is the default place you open whenever you're workin

If you’ve built AI applications in production recently, you’ve probably hit the "Agent Wall." You build a ReAct agent, give it 10 granular tools (search, extract, route, format), a massive system prompt, and tell it to go to work. It feels like magic...until you look at your latency metrics and token bills. Today’s agents act as interpreters. They re-derive the exact same routines from scratch on every single request . They embed massive tool schemas and reasoning histories into every loop. It's slow, it's incredibly token-hungry, and occasionally, they hallucinate tool calls, drop constraints, or get stuck in endless reasoning loops. In a production environment, even occasional errors can be critical failures that waste time and tokens. The problem isn't the ReAct pattern itself. The problem is that we are forcing the LLM to orchestrate low-level, predictable logic that should be deterministic code. We got tired of paying the "reasoning tax" for sub-routines that don't need it. So, we built Sparsi —a framework for shifting complex logic out of your ReAct agent's prompt and into deterministic "Macro-Tools" built as DAGs (Directed Acyclic Graphs). The Macro-Tool Pattern There are two ways to use Sparsi: as an end-to-end solution for a specific task, or to create higher-level tools that plug into your existing agents. The latter is where the magic happens. Instead of giving your ReAct agent 10 tiny, flaky tools and hoping it chains them correctly, you build one highly reliable, deterministic Sparsi DAG to handle that specific sub-routine. You then expose that DAG to your agent as a single Model Context Protocol (MCP) tool. The overall agent still drives the conversation, but it delegates the heavy lifting to a reliable macro-tool. We chose the DAG architecture for three main reasons: Deterministic & Testable: The graph is made of plain code. You only run AI where natural language understanding is strictly required. Parallel by Architecture: Independent branches run co

Schola Interlingua: Free Software for Learning Interlingua IALA Schola Interlingua is a free, open-source platform for learning Interlingua IALA. A practical place to learn The platform is designed around an educational path that brings together lessons, readings, review tools, and progress tracking. Rather than treating learning as a single activity, Schola Interlingua supports a rhythm of studying, reading, reviewing, and returning to the material. Its focus is Interlingua IALA: a language with transparent vocabulary and morphology that rewards attention to structure and usage. Free software and accessible learning Schola Interlingua is developed as open-source software. Its code is available through the Schola Interlingua GitHub organization , making the project available for examination, collaboration, and continued improvement. The platform is available across devices, so learners can use the same educational materials and study tools in the settings that work for them. Explore Schola Interlingua Schola Interlingua website Source code on GitHub Schola Interlingua on the App Store Schola Interlingua on Google Play Chety, for Mandarin Chinese etymology and morphology Ian Blas is a developer based in Buenos Aires, Argentina, building educational software for Mandarin Chinese, Interlingua IALA, etymology, morphology, writing systems, and open-source language learning.

Kubernetes changed infrastructure forever with one idea: you declare desired state, and the system continuously reconciles reality to match it. I wanted that for my codebase, so I built Claude Basecamp and I'm open-sourcing it today. If you're running Claude Code across more than one repo, I'd genuinely love for you to try it, break it, and help me build it out. Try it in one command npx claude-basecamp No install, no database, no config. It discovers the projects Claude Code already knows about and opens at http://localhost:4747 . Runs on macOS, Linux, and Windows. What it does Standing checks, the reconciliation loop. Declare what must always be true, and Basecamp holds it: tests always green -> runs your suite on a cadence; failures dispatch a fix run that commits dependencies current -> npm outdated; safe updates applied, majors escalated to you issue backlog triaged -> gh-powered labeling and stale-closing anything in plain English -> "the README documents every CLI flag" checked read-only, fixed on drift Checks run against deterministic local facts (your real test suite, real npm outdated) wherever possible, zero tokens spent checking. Drift launches a bounded, budgeted, approval-gated convergence run. Repeated failure escalates to a decision card on Home instead of retrying forever. Reflexes, an immune system for your AI. Basecamp mines every transcript for the moments you pushed back (interruptions, "no, don't", permission denials) and turns each into an antibody. Once armed, every Claude Code session on your machine consults that memory before every Bash/Write/Edit action, so a mistake made twice gets blocked machine-wide before it happens a third time. Session Rescue. Notices when a Claude Code session died mid-task and lets you resume the actual dead session, same session ID, full context, as a background run that finishes the job and commits. A persistent manager for every repo. Each project gets an agent with full Claude Code tools plus control over Bas