Docket: a Go terminal document classifier built with Jev
After getting access to Jev, the author built Docket, a Go terminal app that classifies PDFs and images by category, sensitivity, urgency and likelihood of action, with development and testing costing under $1.
Monday came early. Got access to Jev from @typesafeai and built Docket, a Go terminal app for classifying documents. Give it a PDF or image and it tells you the category, sensitivity, urgency, and probability that you actually need to do something about it. OpenAI or OpenRouter handles text extraction, Jev makes the judgments, and Go applies explicit thresholds, shows guidance, and files a local copy. I also wanted the local-data story to be pretty boring in a good way: config.json only stores provider/model/path settings, SQLite stores metadata + Jev results, extracted document text is not persisted, and BYOK credentials live in the OS keychain. The Jev portion of development + testing cost me less than $1. Repo: https://github.com/glamboyosa/docket Marketing: https://docket.glamboyosa.xyz
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