What it does DocJev classifies PDF, DOCX and PPTX documents or splits packets into categorized page ranges, with optional PDF exports.
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How Jev fits LiteParse extracts text locally; hosted Jev decides categories and boundaries, with optional LlamaParse cloud OCR for difficult inputs.
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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.
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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.
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Evidence checked: Sep 30, 2026
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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