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Ana Sayfaya Dön

DocJev is the fastest way to classify and split complex document packets ⚡️. (and the default is fully free and OSS!) I made a sick teaser video below. TY Opus 5.5 🙏 check it out:

Jerry Liu

85,991 subscribers

93,403 görüntüleme • 27 gün önce •via X (Twitter)

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Jerry Liu profil fotoğrafı

Jerry Liu27 gün önce

how i made the video 😂

Ricci Research profil fotoğrafı

Ricci Research27 gün önce

351 bookmarks vs 301 likes is the most honest metric in dev tools, everyone plans to try it right after they finish the other 3,000 repos they bookmarked.

Asaf Mazuz profil fotoğrafı

Asaf Mazuz27 gün önce

Already on my directory 😄 Great tool Thank you for sharing it 🙏🏻

John Rood profil fotoğrafı

John Rood27 gün önce

Two invoices can have every page classified correctly and still get merged into one document. DocJev's default 0.1 boundary-review margin flags uncertain continuations too, not just cuts.

Victor Zhang profil fotoğrafı

Victor Zhang26 gün önce

can it classify between scanned pdf or text-based pdf?

Kaan Demirel profil fotoğrafı

Kaan Demirel27 gün önce

did you make the video with remotion? looks nice

Jerry Liu profil fotoğrafı

Jerry Liu27 gün önce

bro idk i pointed claude code opus 5.5 at it and made it go brrr

Fabian Schreiber profil fotoğrafı

Fabian Schreiber27 gün önce

Really cool. If I understand correctly, you classify full documents and - currently - don't look into classifying chunks/subsections (e.g for RAG), right?

Gavin C. profil fotoğrafı

Gavin C.27 gün önce

This video is super cool! I'd love to know what tool you used to make it.

Roni Rechter profil fotoğrafı

Roni Rechter27 gün önce

Splitting document packets. The least glamorous demo and the one I want.

Shabah profil fotoğrafı

Shabah27 gün önce

this operate on the text layer tho right?

Jerry Liu profil fotoğrafı

Jerry Liu27 gün önce

yep. there are VLM options with llamaparse, which would increase parse latency (though not extract)

Shabah profil fotoğrafı

Shabah26 gün önce

Do you think it will be able to do page level classification of say a form vs a table? I have so many customers asking me how to chunk a table.

George Nick Gorzynski profil fotoğrafı

George Nick Gorzynski27 gün önce

I wonder how this would pair with PageIndex 👀

Gabriel Eisbruch profil fotoğrafı

Gabriel Eisbruch24 gün önce

For packet splitting, we'd validate page coverage separately: every source page belongs to exactly one output, with order preserved. That catches dropped or duplicated pages even when category predictions look sensible.

Lionel Ngendakuriyo profil fotoğrafı

Lionel Ngendakuriyo27 gün önce

We are so done ❤️

aaron profil fotoğrafı

aaron27 gün önce

❌ doctor jev ✅ doc jev

zepa profil fotoğrafı

zepa27 gün önce

So how? Like higgsfield

albs— profil fotoğrafı

albs—27 gün önce

really excellent video. is it remotion?

Brjan | AI Builder profil fotoğrafı

Brjan | AI Builder27 gün önce

DocJev sounds promising, but speed isn't everything, accuracy is key too

Vasant profil fotoğrafı

Vasant27 gün önce

I have captured multiple small size receipt into single photo. ( with the hope something similar solution will appear in future) Can it clarify and split ?

Jatin Garg profil fotoğrafı

Jatin Garg27 gün önce

packet splitting is where most doc systems fail silently. they either over-merge (lose structure) or over-split (create orphans). hard to benchmark.

₮Ɽ₳Vł₴ profil fotoğrafı

₮Ɽ₳Vł₴27 gün önce

dope!

Nichy profil fotoğrafı

Nichy27 gün önce

I need it to be able to distinguish between the layout providers for the same type of document class... for example, it needs to recognize that Layout X belongs to Supplier A and Layout Y belongs to Supplier B. Can it do that?

Vishal Sachar profil fotoğrafı

Vishal Sachar27 gün önce

Free OSS is a boon, but consider how it scales with volume. Performance gains must meet business needs.

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Introducing DocJev - a lightning-fast OSS library for document classification and splitting with jev ⚡️ Give a document alongside some natural language category rules. Jev will predict the document category (classify) or the boundaries between sub-documents (split). It is 6x faster than gpt-5.6-luna with equivalent accuracy. You can choose between different OCR backends: liteparse: the fastest/most accurate free+OSS text parser out there. Perfect for digitalized documents. The speedups vs. luna above are inclusive of liteparse times. LlamaParse: the most advanced VLM-based solution for complex docs. Using this will of course add latency on document preprocessing. But it’s a good option if you want to cache the digitalized representations of documents for a variety of downstream tasks. Check it out: If you want to dive deeper into liteparse or LlamaParse check the links below: liteparse: LlamaParse:

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