jetter

https://modelrift.com/blog/openscad-llm-benchmark/ LLMs are still weak at spatial reasoning, but it gets better. Check out modelrift.com for another alternative

take a look at modelrift.com, it is built around annotating built models by basic pen and arrow tools, works fairly well ('smarter' model is significantly better)

check this out: https://modelrift.com/blog/openscad-llm-benchmark LLMs are getting pretty good at OpenSCAD, especially if they work in agentic mode and can inspect intermediate results.

these small functional prints are exactly where OpenSCAD and LLM generation shines

I agree, my main concern regarding Google AI products is this endless pain around the UX of login / billing / upgrades / product sunsets... but their LLM models are good and Antigravity 2.0 is not that bad either (unless you lost all you Antigravity 1.0 setup and projects - like many people did)

If you like this, you should definitely check modelrift.com which allows to build awesome cad models thanks to OpenSCAD and smart AI assistant.

Community built examples: https://modelrift.com/models

Did you try modelrift.com ? Its openscad + ai but way more convenient to preview results in realtime and iterate via annotated screenshots

try modelrift.com ? Llms are bad at spatial understanding but you can steer them using annotated screenshots ("annotation mode" of modelrift) and get something working: https://modelrift.com/models/cable-conceal-box-with-wall-mou...

https://modelrift.com/models/customizable-liquid-funnel

Also check out modelrift.com which is based on openscad foundation. See the dynamic customizer which allows to edit any model parameter, re-render and get .stl: https://modelrift.com/models/customizable-liquid-funnel - it works _completely_ in your browser by using WASM

I have just added Mt Fuji to quick links.

proper sessions page is live: https://modelrift.com/changelog/v0-3-2

let me know how it goes!

building a benchmark is a great idea, thanks, maybe I will have a couple of days to spend on this soon

right, I need to fix this one

Thank you for this feedback, very valuable! I am using Bambu as well - perfect to get things printed without much hassle. Not sure if direct push to printer is possible though, as their ecosystem looks pretty closed. It would be a perfect use case - if we could use ModelRift to design a model on a mobile phone and push to print..

it is interesting that the video demo is generating .stl model. I run a lot of tests of LLMs generating OpenSCAD code (as I have recently launched https://modelrift.com text-to-CAD AI editor) and Gemini 3 family LLMs are actually giving the best price-to-performance ratio now. But they are very, VERY far from being able to spit out a complex OpenSCAD model in one shot. So, I had to implement a full fledged "screenshot-vibe-coding" workflow where you draw arrows on 3d model snapshot to explain to LLM what is wrong with the geometry. Without human in the loop, all top tier LLMs hallucinate at debugging 3d geometry in agentic mode - and fail spectacularly.

If you like OpenSCAD, you should check https://modelrift.com which is an OpenSCAD browser-based IDE which uses LLM to generate .scad and instantly shows the .stl 3d model result via 3d model viewer. Since AI models are still not good at openscad, the useful feature of modelrift is the "screenshot-powered" iteration where human annotates visual problems and sends it back to AI assistant to fix, all using hotkey shortcuts.

A list of sandboxing techniques and products: https://github.com/restyler/awesome-sandbox

I am running a web scraping API ScrapeNinja https://scrapeninja.net. 10K+ subscribers.

It is a (rather messy) node.js codebase. Two rendering engines, including a hacked puppeteer package with stealth mode for better success rate. A big set of proxy providers under the hood. Bootstrapped.

I use Clickhouse to store close to 1TB of API analytics data (which would be 10TB in MongoDB, Clickhouse has insane compression ) and it's a wonderful and stable SQL-first alternative to DuckDB - which is a very exciting piece of software, but is indeed too young to embed into boring production. The last time I checked DuckDB npm package, it used callbacks instead of awaits..

Interesting test suite, thanks! I have tested scrapeninja.net via https://scrapeninja.net/scraper-sandbox and I got { "puppeteerEvaluationScript": "OK", "webdriverPresent": "OK", "connectionRTT": "OK", "refMatch": "OK", "overrideTest": "OK", "overflowTest": "OK", "puppeteerExtraStealthUsed": "OK", "inconsistentWebWorkerNavigatorPropery": "OK", "inconsistentServiceWorkerNavigatorPropery": "OK" }

and ip range of "us" geo proxy gives is_abuse: true. Consider this to be okayish though, given that this is a default proxy pool.

scrapeninja.net /scrape-js endpoint scrapes company pages of g2 without big troubles (with "us"/"eu" proxy geo in their online sandbox: https://scrapeninja.net/scraper-sandbox ). They also have /scrape which is much faster because it does not bootstrap real browser, and bypasses CloudFlare TLS fingeprint check: https://pixeljets.com/blog/bypass-cloudflare/

If you are a minimalist, and are using VS Code, try https://marketplace.visualstudio.com/items?itemName=humao.re... which is a pure text syntax to describe API requests, and execute them right from the editor window. I now have api.http text file in every API-first project I am building and I love it.

For me, it is always a pain to write and test cheerio code unless I was doing it on the previous week. The syntax of cheerio is somewhat similar to jQuery, but this is still node.js, and not "real" DOM.

I was suffering every time I was googling for "Cheerio quick examples", so I have built a cheerio sandbox to quickly test cheerio syntax against various test inputs. This is already helpful for myself and saves me up to 15-30 minutes on every simple scraper I am writing, I think, just because I have working selectors samples at hand and I can quickly test my new selectors.

I have built an online tool which does just one thing: traces a handwritten signature.

Thank your for the invitation! Will definitely consider submitting my story.

Thank you for what you guys do. Altinity blog and videos are an outstanding source of practical in-depth knowledge on the subject, so much needed for Clickhouse recognition.

https://github.com/meilisearch/MeiliSearch gets a lot of traction recently. There are also Sphinx and its fork https://manticoresearch.com/ - very lightweight and fast.

I've mentioned Pinot and Druid briefly in 2018 writeup: https://pixeljets.com/blog/clickhouse-as-a-replacement-for-e... (see "Compete with Pinot and Druid" )

Nice! Adding this to the post, thanks for the link!

Yep, do you guys have a writeup on this? Altinity actually mention Contentsquare case in their video, here: https://www.youtube.com/watch?t=2479&v=pZkKsfr8n3M&feature=y...