Каталог продуктов
Отслеживается продуктов: 116
Capgo
Мгновенные обновления для Capacitor-приложений. Выпускайте исправления за минуты, а не недели. Отправляйте OTA-обновления пользователям без задержек App Store.
OpenAlternative
OpenAlternative — каталог open-source альтернатив проприетарному софту. На сайте собраны проекты из разных категорий с информацией о возможностях, стеке технологий и метриках GitHub. Платформа монетизируется через платные размещения и партнёрские ссылки.
SubSmith
I've been learning Japanese for a few years and kept running into a similar problem. I'd find a video I wanted to learn from, hear a useful sentence, and then realise that turning that sentence into something I could study later was both time consuming and draining at times. I would end up jumping between a video player, subtitles/transcription, a dictionary, screenshots, audio clips and Anki. So I built SubSmith to bring that workflow together. You can drop a video or audio file into it, generate a transcript locally and then use the transcript alongside the media to: * look up words and sentences * replay individual lines * edit the transcript * save useful sentences with their original context/audio * export them as Anki cards The important part for me is that it works with your own media. It isn't tied to a particular streaming service or library, so I can use the random anime episode, podcast, lecture, etc. that I'm actually interested in studying. It's an offline-first desktop app, and transcription happens locally rather than sending the media to a transcription API. I'm sharing it here because I'm now more interested in finding out where this workflow breaks down for other people rather than adding features randomly now that I have solid core/base. For example: * Would you actually save sentences from your own media? * Which part of this process feels like too much work? * Does having the audio/context attached make creating an Anki card more useful? * Would you prefer this to work inside your existing video player/browser? * Is installing a desktop app a significant barrier? * And does requiring an account before starting the free trial make you give up? The current version does require an account to start the trial, and I'm trying to work out whether that's meaningful friction for the people who would actually use this. It's free to try, and I'd particularly appreciate feedback from people who already learn languages through their own videos, anime, films, podcasts or other media. I'm the developer, so I'll be around in the comments to answer questions and discuss how it works. https://subsmith.app
Ancestree
Every time I talk to my older family members, especially my grandparents, I find out a new super interesting fact about them. Last week: my Croatian grandfather served in the French marine corps... Not worth mentioning I guess. I realized that these stories are passed down only by re-telling them. Just think about how much you don't know about your family from 2 generations ago. For this reason, I created ancestree.marindedic.com It's a really cool family tree creation app, where each person gets their own book. Inside it, write what they did, what happened to them, what they were like... whatever you want. Little biographies of your loved ones. Apart from exporting normal and detailed versions of your family tree, you can even export someone's chapters as one long biography. Of course, open-sourced, no account, no server. Nothing you draw or write ever leaves your browser.
Keenable
Hey HN! We built https://keenable.ai, a different web search API for AI agents. Keenable searches our own 100B+ page index. We are focused on low cost and latency (p95 <250ms from us-east). We don’t believe in benchmaxxing, so we open-sourced our internal benchmarking suite, NEEDLE (available at https://keenableai.github.io/needle): a live benchmark that compares Keenable with other search APIs on fresh agent-like queries. I spent seven years at Amazon as a scientist working on web grounding for Alexa/AGI, and my co-founder Andrey previously led search at Yandex. We started Keenable because agents search differently from humans, and we wanted to build around those patterns directly. The API is available now and we provide a free allowance of 100,000 requests a month. It also exposes a novel SQL-like interface to the web, which is useful for structured extraction and agent workflows. Happy to answer questions about the index, crawl, ranking, latency, or benchmarking.
Structural code grep across public GitHub repositories
Codemod grep searches public code by syntax and structure, not just text or regex. Use ast-grep patterns to find code by shape across repositories.
Kandelo
Kandelo is an open-source, Wasm-based multi-process kernel that runs POSIX programs in browsers and Node.js. Kandelo is still experimental, but it already runs a substantial range of existing software. Do you have use cases for this? We are trying Kandelo as a new foundation for WordPress Playground which runs server-side WordPress entirely in the browser. Kandelo also looks promising as a sandbox for running agents in the the browser and on the command line. On the side, we've been playing with porting games and desktop environments and even compiling runnable programs within Kandelo. Yet it feels like there are many possibilities we haven't considered. How would you like to use something like this? Demos: Some notes: The demos have been tested in desktop browsers. Unfortunately, YMMV on mobile today. Some of the disk images are large (~50MB) and may take a while to boot initially. Main set, with Shell (bash, vim, nethack, and more), Nginx, PHP, WordPress, and Doom: https://kandelo.dev/20260819-demo/ LÖVE game engine: https://kandelo.dev/20260819-demo-love/ SNKRX running under LÖVE: https://kandelo.dev/20260819-demo-love/?vfs=love-snkrx-abi44... Commander Keen running in DOSBox: https://kandelo.dev/20260819-demo-dos/?demo=keen LXDE desktop PoC: https://kandelo.dev/20260819-demo-lxde/?demo=desktop-lxde Background I wanted an authentic OS-level foundation for running systems software in the browser and started this as a vibe-coded exploration. I figured it would end up being too slow and that we would have to offer many different ways to compromise default POSIX behavior to get anything usable. But after weeks of fighting agents, insisting on genuine POSIX compatibility as the default, I was surprised at how well the system worked without those compromises. Nginx, PHP, Python, Ruby, Redis, and even MariaDB were able to be built using the SDK with minimal hacks. Then we started porting games, having fun, and playing to see how far we could push it. Notes on architecture: There is a central, single-worker kernel, aiming to provide all supportable POSIX syscalls. Each process is a dedicated worker with independent memory. Each process thread is a dedicated worker that shares memory with threads from the same process. Syscalls are done with the process SharedArrayBuffer and the Atomics API. fork() is supported. The system is centered around virtual file system (VFS) images, and the VFS can contain lazy references to programs that may or may not be used. Vim is such a reference in the shell demo. On GitHub: https://github.com/Automattic/kandelo
WaveHouse
While building an IoT telemetry solution, we ran into hurdles with Clickhouse. For one, you can't insert quickly AND durably into Clickhouse without setting up something like Kafka, which gets complicated for quick projects wanting to make use of Clickhouse's powerful features. Then, trying to actually query Clickhouse and show data in a UI required a whole backend API to handle auth and permissions. We figured that all these parts together – fast, durable ingest, row-level and column-level security and roles, and realtime streaming – were a lot of scaffolding to have to rebuild for every project we wanted to use Clickhouse in. So, we built them all into a single Go binary to be deployed alongside Clickhouse, to help lower Clickhouse's barrier to entry. We call it WaveHouse. Would love any feedback as we work on improving and adding more features to this OSS project!
Huzzah
Hello everyone. I've been working on this experimental editor called Huzzah. I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself. I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this interaction paradigm where you: 1. write pseudocode in whatever way makes the most sense to you 2. on save, the editor synchronizes your work to real source code 3. the pseudocode is persisted alongside the generated code, making your prompt effectively a stored record of intent. It may not work for every use case, but in my initial playthroughs I've found it very enjoyable. Right now it's just a proof of concept - installation instructions are here in the readme: https://github.com/danielvaughn/hz You can also watch a video of it in action here: https://x.com/danielvaughn/status/2090456808431165715 Cheers!
Open-source Stripe Connect alternative
Hey, I'm Ben. I built Zoneless because I was paying so much to use Stripe Connect on my own marketplace. The fees were really, really bad, and it was also limiting in terms of the seller countries I could onboard. To give you an idea, I was paying around $9,000 per month in fees just to run payouts. Using Zoneless, that cost goes down to around $6. I've been using it personally for the past few months, and onboarded 5,000+ sellers and done 3,000+ payouts. 74% of new sellers on my marketplace choose Zoneless over Stripe, which is really interesting. I appreciate crypto and stablecoins are a bit of a touchy subject, but for this use case of sending global payouts cheaply, it's perfect. The project is open source with an Apache 2.0 licence, which means there's the benefit of no lock-in and no risk of your account getting flagged or shut down. It also has an almost identical API and dashboard to Stripe. Would love to hear any feedback you may have in the comments.
I trained a 125M model to autocomplete piano on-device
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
Online SNMP MIB database
Show HN: Online SNMP MIB database - upload/view your own MIBs