Jev – A curation of Jev demos on X, tools, skills, and integrations

Jev – A curation of Jev demos on X, tools, skills, and integrations github.com

Jev demos, projects, SDKs and skills, with source links and a curated X gallery. - Amal-David/awesome-jev

95 points•frostbyte7•8 days ago•34 comments•

#jev #tools #skills #demos #curation #integrations #jev demos #contribute

34 comments

https://x.com/dWeaths/status/2102415625301717065 - Here's my use case of jev, being able to accurately detect nouns (with adverbs, adjectives etc.) in realtime as the user is typing it, genuinely feels like it's running locally with how fast it comes back. I've sent over 1000 requests to Jev and its cost me $0.01 (probably rounded up!).

rahimnathwani8 days ago

I'm curious why you didn't use a spaCy for this. It would probably be faster, and you'd avoid a third party API dependency.

davidweatherall8 days ago

For my specific example: "the tall dark handsome man wanders into a dark gloomy bar. he orders the biggest beer in the world and sits down on a bar stool surrounded by irish dancers" spacy splits out "the biggest beer" and "the world", whereas I want "the biggest beer in the world" to be the singular noun.

AStrangeMorrow8 days ago

I mean now with modern LLMs a lot of good packages and tools get forgotten about. When you have hammer everything looks like a nail. Even if said "old" tools are actually orders of magnitude faster, and sometimes better too for that specific task. (And I remember spacy being basically SOTA for generalist NLP tasks not that long ago, like 2020/2021).

levmiseri8 days ago

I had an idea for a 'write without space, basicallylikethis' and Jev (given how cheap it is) just being asked after every key press where inserting spaces (or making typo correction) would make sense.

The demo is here: https://levmiseri.com/nospace

raahelb8 days ago

This one is cool as hell

And so, I typed "Thisoneiscoolashell", and got "This one is cool a shell" hahaha

Great idea, and it's really quick

levmiseri8 days ago

Thanks! Made some updates to it to strengthen the corrections/splits. Should work substantially better now.

viccis8 days ago

Honestly just getting it integrated into mobile phone swipe keyboards would be a godsend. If I type "We need to get going " and then swipe the word "now", I really do not think "mower" should be the word it chooses. Present a set of swipe-based likely words and the preceding text message to Jev, or similar model, and pick its highest prob word.

liquicity8 days ago

Initial personal use case (on my side project https://mealplannr.io/lists) is lists have a "smart categorise" button to group items into 20 or so preset lists.

Previously this took up to ~30-60 seconds using deepseek v4 flash (even with a medium list size) - Jev is <1 second @ same cost with typesafe guarantee

As a bonus I can also instantly categorise new items - rather than sending them into an "unknown" category (and waiting for user to have to click "categorise" again)

suraj_phanindra8 days ago

i built wellposed as a plugin/skill which works with any agent (https://github.com/suraj-phanindra/wellposed) to ensure your agent understands how to choose the right kind of jev request and format it correctly not just for syntax but for completeness and correctness. it is well-documented in the "jagged-ness" docs (https://docs.typesafe.ai/model-jaggedness/jev-1.13) that typesafe include on their docs page that the absence of essential options can cause jev to choose the wrong option with high confidence (it cannot choose what it cannot see in the request) - so the responsibility to ensure whatever the intent behind your jev request is - it is captured correctly with the right states and options for jev to pick from falls on the user. wellposed should ideally make your agent better at converting NL intent into jev requests. please try and give me feedback. appreciate it!

lewisjoe8 days ago

Can someone ELI5 me why Jev class models matter?

Note: Not the technical side, but as an end user of LLM APIs.

AStrangeMorrow8 days ago

Basically compared to standard LLM models it is an order of magnitude cheaper and faster. (Note: I didn't get to actually try jev yet, just looked at demos/specs/pricing etc)

You can definitely do similar things with say hosted LLMs + a lib like outlines , or with API models and the proper output validation layer, but again way slower and more expensive.

And on the opposite side you can train dedicated classification models that will be even cheaper and faster to run than jev. But, well, you need to train them (costly, time consuming, and data might be hard to come by depending on target). Here you are a nice zero-short system, that can handle complex/messy data out of the box.

lewisjoe8 days ago

Thanks. How reliable is the world knowledge? Say, I use it as a delegation router for picking the best model for a task - how can I be confident it's doing that with enough intelligence?

When I use traditional LLMs I get some sense from the flagship-ness and regular usage. How do we get such confidence for Jev like models?

thebitguru8 days ago

I was wondering about the same and found this video very helpful. It may not be truly ELI5, but close enough: https://www.youtube.com/watch?v=tTnUcSj-QPA

lewisjoe8 days ago

That helps, thanks.

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