nvbn/mrw.wtf — explained in plain English
Analysis updated 2026-08-04 · repo last pushed 2017-03-22
Find the perfect reaction GIF by typing a natural-language description of how you feel.
Share reaction GIFs directly in Telegram chats via a bot.
Search for reaction GIFs from a web browser or mobile app on Android or iOS.
| nvbn/mrw.wtf | netb258/defn-system | benfleis/throttler | |
|---|---|---|---|
| Stars | 6 | 7 | — |
| Language | Clojure | Clojure | Clojure |
| Last pushed | 2017-03-22 | — | 2015-01-28 |
| Maintenance | Dormant | — | Dormant |
| Setup difficulty | hard | moderate | easy |
| Complexity | 4/5 | 4/5 | 2/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
No setup guide or usage instructions are included, and the project requires Clojure, Elasticsearch, and multiple coordinated services to run.
This repository builds mrw.wtf, a service that helps people find the perfect reaction GIF. You know the feeling, someone says something online and you want to reply with a GIF that captures your reaction. Instead of scrolling endlessly through GIF libraries, this project lets you search with natural language and get matched to a relevant clip. The project is actually a collection of smaller services working together. One piece scans Reddit and Imgur to gather GIFs. Another analyzes the text you type so the system understands what kind of reaction you're looking for. A public API ties everything together, and there's a web frontend plus mobile apps for Android and iOS. There's also a Telegram bot, so you can find and share GIFs directly in chat. The search itself relies on Elasticsearch, which is a specialized tool for quickly finding relevant results from large collections of data. The main audience is people who frequently communicate with GIFs, anyone who hangs out on Reddit, Telegram, or similar platforms and wants a faster way to find the right reaction. "MRW" stands for "my reaction when," a common phrase people use when posting reaction GIFs, which is where the project gets its name. The README doesn't go into much detail beyond listing the components and mentioning Elasticsearch. There's no setup guide or usage instructions included, so getting it running would require some familiarity with the underlying technologies. The choice to split everything into separate services suggests the project was designed to be modular, but the README doesn't explain the reasoning behind that architectural decision.
A reaction GIF finder that lets you search with natural language and get matched to the perfect clip. It gathers GIFs from Reddit and Imgur and serves them through a web app, mobile apps, and a Telegram bot.
Mainly Clojure. The stack also includes Clojure, Elasticsearch, Telegram Bot API.
Dormant — no commits in 2+ years (last push 2017-03-22).
The README does not include any license information, so the default terms of copyright apply and you should contact the author before using this code.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
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