标签：#ha

Turn LibreOffice .odt files into publishable file bundles for Kindle

This is a submission for the Hermes Agent Challenge What I Built Onyx is an autonomous infrastructure operator running 24/7 on my droplet. He manages my entire stack: 6 Next.js deployments, 5 Docker containers, a Minecraft server, fail2ban, Nginx, and UFW. He also helps me write my undergraduate thesis. The difference from every other "AI agent" project I've seen: Onyx doesn't wait for commands. He surfaces problems, patches vulnerabilities, and pushes work forward on his own. When I wake up, there's a session log waiting for me, not a to-do list. The core idea: graduate an AI agent from assistant to operator . A chatbot with tools bolted on doesn't cut it. I wanted something that runs infrastructure while I'm eating dinner, asleep, or in class. Demo Onyx operates through Discord. A normal week: 🔴 3 AM — gateway process failure, no wake-up required A gateway process had a stale PID. Onyx detected it, diagnosed the root cause, restarted it cleanly, and wrote a session log. I found out in the morning. Zero human intervention, zero downtime. 🟡 Dinner — 9 CVEs found across Docker containers While I was eating, Onyx ran a routine audit, found 9 CVEs, rebuilt 3 container images from fresh base images, patched Python dependencies, hardened fail2ban (ban time: 600s to 24 hours), and verified every container came back healthy. 🟢 "Fix it" — two words, full tunneling deployment My friends in Indonesia couldn't connect to the Minecraft server because their ISPs use carrier-grade NAT. I sent Onyx "fix it." He researched solutions, selected playit.gg, installed the tunneling agent, configured a systemd service, and optimized TCP keepalive parameters. All autonomous. 🧠 Accountability loop Onyx noticed I kept asking for things but not acting on the output. He surfaced it: "You keep opening new loops and not closing them." He was right. Now when I open a loop, Onyx tracks it until it's closed or explicitly shelved. 📚 Thesis research partner I'm finishing my undergraduate thesis on e

This is a submission for the GitHub Finish-Up-A-Thon Challenge What I Built GlowStore — a full-stack MERN e-commerce store (React + Redux + Express + MongoDB). Back in 2023 I built this as my university Web Engineering final project. I ran out of time, handed in what I had, and never touched it again. When I reopened it for this challenge I found something funny: the backend was basically finished — JWT auth, products, orders, reviews, search — but the React frontend never actually talked to it. It was a good-looking shell with fake logic bolted on. So "finishing it" meant connecting the two halves and making it a real store you can actually shop in. Repo: https://github.com/hashaam-011/Web-Engineering Demo Before — the entire app was just a fake login screen. Typing anything (or nothing) and clicking "Log in" flipped a boolean and "logged you in": After — a working storefront with products from the database: A real product detail page (was literally <h1>DetailsPages</h1> before): You can run it yourself in two terminals (no database setup needed — it boots an in-memory MongoDB and seeds itself): cd backend && npm install && npm start # http://localhost:4000 npm install && npm start # http://localhost:3000 Demo login: user@example.com / 123456 — or register a new account. The Comeback Story Here's what the project looked like before , and what I changed: Before After Login dispatched a boolean and ignored your credentials Real login/register against the API with JWT + bcrypt Frontend never called the backend (no axios anywhere) Axios client with token injection; products load from MongoDB Product details page was <h1>DetailsPages</h1> and wasn't routed Full details page (image, price, stock, rating) routed by slug Cart was local-only; "checkout" button did nothing Persistent cart → checkout → real order placed and saved Backend had a reviews endpoint the UI never used Product reviews: read them and post your own with a star rating Only 3 routes; most of the app was

Started propfirmpinescripts.com a while back selling pine script strategies for futures prop firm traders. Figured I would share some of what worked and what has not. The problem I was solving I was actually trading on Apex myself and kept running into the same thing. Every pine script strategy I found online was not built for prop firm rules. Daily loss limits not enforced in code. No end of day flatten. Blew an evaluation partly because of it. Figured other traders had the same problem. Coded the rules myself, then decided to sell the scripts. What I built Pre-built pine scripts for 4 instruments: GC (gold futures), MES (micro S&P), MNQ (micro Nasdaq), CL (crude oil). Each one has daily loss lock, EOD flatten, win lock coded in. You can configure the limits for different firms without touching the core logic. Priced at $50 for a single script or $150 for all 4. What actually moved conversions Adding real payout screenshots. Like actual Apex payout certificates from traders who passed using the strategies. Before I did that — traffic but weak conversions. After — noticeably better. Prop firm traders do not trust backtest results at all anymore. Too many people have gamed them. A real funded account payout is the only thing that actually means something to them. Where things are at Still early. Revenue is real but small. Building more SEO content, getting into prop firm communities, and eventually a subscription tier for updates when firms change their rules. If you are a dev with trading knowledge this space is underbuilt.