完整作品展
技术栈
60 projects
在你的社区搜索本地企业，发现他们的故事和优惠。
@localmama4u · X
将菜单PDF转换为专业数字菜单，包含图片和5种语言翻译。
@juancastillamar · X
Hi Esther, I’m a frontend developer working in seo for let’s connect and keep growing!
浏览附近餐厅的每日鸡翅特价、啤酒优惠和欢乐时光。
@WingBeerSpecial · X
- Discover daily specials at restaurants near you. Currently limited to Ontario Canada. Let us know if you like to concept and want to see coverage in your area next!
扫描二维码浏览餐厅数字菜单并订餐，无需下载应用。
@bhojan_qr · X
Paper menus belong in a museum. 🏛️🚫 We just launched BhojanQR. Beautiful digital menus, zero wait time, and seamless ordering—all from a single QR scan. 🚀🍽️ Live Link : #BuildInPublic #SaaS #FoodTech #BhojanQR
在Davini's Food Bank浏览菜单、下单和预订座位。
@Hafid_raji_ · X
搜索餐厅，发现当地人真正吃饭的地方，避免旅游陷阱。
kingchesco · HN
I know $90 for a dining app sounds absurd. And it’s not even an app; it's a wrapper for an LLM. But it is how it is built that makes it so expensive. I had to make a whole API just to call it (which because its own SAAS). All just to bypass dumb google reviews. Google Maps and reviews send people to places optimized for tourists and good copywriters. To find actual local hole-in-the-walls algorithmically, I had to first build that api (called BWENDI), a "spatial gravity" engine using 100GB+ of tweaked OSM, GeoNames, and other proprietary data. Instead of aggregating reviews, it mathematically calculates foot-traffic, throughput, transaction stats, and economic criticality among other factors. Bwendi is A Python/Node ETL pipeline feeding an LMDB-backed context API. It uses a proprietary 1MB binary grid served via Cloudflare Workers for millisecond edge reads with near-zero overhead, hosted in Switzerland. This was done of course to get the purest location context around every street
改变字母逐个拼出目标单词的免费文字谜题游戏
poople game — 字母拼字游戏，逐个添加字母直到拼出目标单词
