What you can build with it

What it does

DocJev classifies PDF, DOCX and PPTX documents or splits packets into categorized page ranges, with optional PDF exports.

Evidence 1 ↗

How Jev fits

LiteParse extracts text locally; hosted Jev decides categories and boundaries, with optional LlamaParse cloud OCR for difficult inputs.

Evidence 1 ↗

Getting started

Install the Python package with uv, export TYPESAFE_API_KEY, and run docjev classify or split with category rules. Office formats require LibreOffice.

Evidence 1 ↗

Scope and limits

Local parsing does not mean offline inference: normalized text reaches the decision provider. Category probability and provider confidence are distinct and are not claimed to be calibrated.

Evidence 1 ↗ · Evidence 2 ↗ · Evidence 3 ↗

Repository description

A very fast document classifier/splitter using Jev

Project facts

Relationship to Jev
Jev application
Evidence
Documented
Language
Python
License
Apache-2.0
Origin
Original repository
Repository status
Not archived
Created
2026-09-19
Last code update
2026-09-21
GitHub stars
473
Evidence checked
Sep 30, 2026
Metadata checked
Sep 29, 2026
Check status
Up to date

Stars measure the whole repository, including work unrelated to Jev.

Evidence and scope

Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.

Evidence commit: c7abe276a970605feb9cb8b27513365b6c10726e

Discovered through: typesafe-field-guide.

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