Show HN Today: Top Developer Projects Showcase for 2024-09-22
Explore the hottest developer projects on Show HN for 2024-09-22. Dive into innovative tech, AI applications, and exciting new inventions!
Summary of Today’s Content
Today’s summary highlights several innovative projects featured on Show HN. MeetCaddy offers a browser extension for automatically saving Google Meet chats. An updated KFC menu website provides current prices. Simple File Compressor enables hassle-free file size reduction online. Model2Vec enhances sentence transformers for faster, smaller models. Pinnit is an Android app for managing notifications effectively. Other projects include an email parsing tool, dynamic OG image generator, and a fast prefix search server. Each project aims to solve specific user needs, inviting feedback from the community.
1. Show HN: MeetCaddy – Automatically save Google Meet chats
URL: https://meetcaddy.online/
Author: dkraj
Description: Few days ago, I was searching for a document url that I received from my mentor in google meet.
Unable to find that motivates me to solve this problem and I developed a browser extension that automatically saves messages sent in a google meet.
Features:
- Automatic Chat Capture
- Simple Setup
- All data stored in your local device storage
Feedbacks and criticism are always welcomed…
Popularity: 1 points | 0 comments
What do you think about this project? Share your thoughts in the comments!
2. Show HN: Most updated KFC menu with prices
Author: victor_cl
Description: Show HN: Most updated KFC menu with prices!
Popularity: 1 points | 0 comments
What do you think about this project? Share your thoughts in the comments!
3. Show HN: Simple File Compressor
URL: https://github.com/39zde/simple-file-compressor
Author: 39zde
Description: A tool to reduce the file size of your files. Free online, local, tracking-free, advert-free file compression. Simple and fast.
Now, that the following browser features are implemented by the major vendors:
- Resizable ArrayBuffers (since July 2024)
- transfer ArrayBuffer to a fixed length (since March 2024)
- Compression Streams (since May 2023)
nothing stands in the way of selecting a file, compressing it with the CompressionStream API, creating an archive and downloading it.
Nothing special per se, but it’s another thing, that can now be done using only the browser.
Popularity: 1 points | 0 comments
What do you think about this project? Share your thoughts in the comments!
4. Show HN: Mysterious Postgres Connection Bug
URL: https://medium.com/@avirajkhare00/mysterious-postgres-connection-bug-052bc04999b9
Author: avirajkhare
Description:
Popularity: 1 points | 0 comments
What do you think about this project? Share your thoughts in the comments!
5. Show HN: Open-source dynamic og-image to your blog / website
URL: https://ogcool.vercel.app/
Author: anduc
Description: Inspired by https://og-image-meme.vercel.app/ and https://github.com/steven-tey/og, I made this tool to create dynamic OG images for websites and blogs, with an typescript SDK that makes embedding easy. Check out source code here: https://github.com/ducan-ne/ogcool
Popularity: 3 points | 1 comments
What do you think about this project? Share your thoughts in the comments!
6. Show HN: Formulaer – Free, simple and clean forms
Author: drikerf
Description:
Popularity: 4 points | 1 comments
What do you think about this project? Share your thoughts in the comments!
7. Show HN: Model2Vec: make sentence transformers 500x faster on CPU, 15x smaller
URL: https://github.com/MinishLab/model2vec
Author: stephantul
Description: Hi HN!
We (Thomas and Stéphan, hello!) recently released Model2Vec, a Python library for distilling any sentence transformer into a small set of static embeddings. This makes inference with such a model up to 500x faster, and reduces model size by a factor of 15 (7.5M params or 15/30MB on disk, depending on whether you use float16 or float32).
This reduction of course comes at a cost: distilled models are a lot worse than their parent models. Even so, they are actually a lot better than large sets of conventional static embeddings, such as GLoVe or word2vec-based models, which are many times larger. In addition, the performance gap between a Model2Vec model and a sentence-transformer ends up being smaller than you would expect, see: https://github.com/MinishLab/model2vec/tree/main?tab=readme-… for results. Fitting a Model2Vec does not require any data, just a sentence transformer and, possibly, a frequency-sorted vocabulary, making it an easy solution to implement in whatever workflow you have lying around.
We wrote this library because we separately got a bit frustrated with the lack of options if you need extremely fast CPU inference that still works well. If MiniLM isn’t fast enough and you don’t have access to a GPU, you’re often resigned to using BPemb, which is not flexible, or training your own GLoVe/word2vec models, which requires lots of data. Model2Vec solves all of these problems, and works better than specialized static embeddings trained on huge corpora.
We spent a lot of time thinking about how the library could be easy to use and integrate into common workflows. It’s a tiny thing: we’d rather make only a few generic functions that work well instead of having a ton of integrations.
Please let us know what you think. We’re very interested in getting feedback from you. We’re already using this in our own projects, and ultimately built this because we kind of needed it, but we’d be happy to hear from you if you have interesting use-cases or questions.
Finally, If you think this sounds a lot like WordLlama, which was featured last week. It is! We were working on this in “stealth mode” for a while, since May, so I guess we and the WordLlama authors came up with the same idea at about the same time. We directly compare our models to WordLlama in our experiments. In short: WordLlama does a little bit worse, and is not unsupervised or multilingual, so it’s more difficult to adapt to new domains than Model2Vec.
Have a nice day!
Popularity: 6 points | 2 comments
What do you think about this project? Share your thoughts in the comments!
8. Show HN: Inbound Email (SMTP) to Webhook
URL: https://github.com/sendbetter/inbound-email
Author: martinkrivosija
Description: Here’s my first (hopefully of many) open source release. A minimal script to receive emails via SMTP, parse content (including headers), store attachments in Amazon S3, and forward email content to a webhook.
I use it to power DMARC report storage and email content testing.
Some of the big email API providers have inbound APIs but costs can rack up fast if you’re using them at scale. Hence why I built this.
https://github.com/sendbetter/inbound-email
Features
- SMTP server to receive emails concurrently
- Parses incoming emails using mailparser
- Uploads attachments to Amazon S3
- Forwards parsed email content to a specified webhook
- Configurable via environment variables
- Handles large attachments gracefully
- Queue system for processing multiple emails and webhook requests simultaneously
Popularity: 2 points | 1 comments
What do you think about this project? Share your thoughts in the comments!
9. Show HN: A Site I Made
Author: atulseth22
Description: I created a website to analyze large legal documents and research papers after spending a week to understand how to integrate with Open AI.
Popularity: 2 points | 0 comments
What do you think about this project? Share your thoughts in the comments!
10. Show HN: Fast prefix search server in Golang
URL: https://treds.io/
Author: absolute7
Description:
Popularity: 3 points | 1 comments
What do you think about this project? Share your thoughts in the comments!
11. Show HN: Pinnit – Pin notes and notifications in Android notification panel
URL: https://play.google.com/store/apps/details?id=dev.sasikanth.pinnit2&hl=en_US
Author: its_sasikanth
Description: Pinnit is a freemium app (no ads, one-time payment with a 14-day trial) that allows you to keep a log of your notifications, and pin them or schedule them to act as reminders on Android. It features a beautiful Material 3 design with smooth transitions and motion between screens and states. It also has a customisable color palette for generating Material 3 dynamic themes.
Features
- Create and pin your own notifications
- Manage your notifications with a history log, search & filtering options
- Schedule notifications and add reminders
- Add notes to third-party notifications
Privacy is an important thing when dealing with notifications, so here is the app privacy policy (https://sasikanth.dev/privacy-policy-pinnit/).
TLDR: All notifications are local to the device and nothing ever syncs with any backend or third-party service other than crash reports and billing.
We have more things planned for the app to build, so looking forward to that. Give Pinnit a try and let us know what you think. Thank you :D
Popularity: 1 points | 0 comments
What do you think about this project? Share your thoughts in the comments!
Conclusion
Today’s Show HN roundup showcases a diverse range of innovative projects. From AI-powered tools to creative coding solutions, these projects reflect the dynamic nature of our tech community. Which project caught your attention the most? Let us know in the comments!
Tags: #ShowHN #TechInnovation #DeveloperProjects #AI Applications #Open Source Software