Lazy Tidier: I Taught an Open-Weight Model to Clean My Downloads Folder

Описание и применение

Lazy Tidier – это CLI на Python, который сортирует папку загрузок, используя правила расширений и открытый LLM для неоднозначных файлов. Он безопасен, поддерживает dry‑run, откат и обеспечивает конфиденциальность.

Задача

The author’s Downloads folder was cluttered with mixed file types and ambiguous names, making manual cleanup tedious.

Результат

On a 19-file test set, 11 files were processed by the LLM and all categories matched manual review; dry-run completed in ~8.6s.

Рабочий процесс

• Scan folder non-recursively
• Apply extension-based rules to obvious files
• Send ambiguous PDFs, TXT, MD, DOCX to open-weight LLM with filename and up to ~500 chars
• Validate LLM JSON response, sanitize names, enforce privacy guard
• Generate dry-run plan and display table
• If --apply, write undo log and move files into category subfolders
• If --undo, reverse last apply using undo log

Доказательства

Lazy Tidier is a Python CLI that sorts a messy folder using simple rules first and an open-weight model only for ambiguous files.

Источник

Most of the work needs no AI at all. Rules based on file extension sort the obvious files for free.

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Only the ambiguous ones (PDFs and text notes) go to an open-weight model.

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A normal run is a dry-run: it only prints what it would do.

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--undo reverses the last run, restoring the original names too.

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The privacy guard: files whose names contain any of 14 sensitive whole words are sorted locally and never sent to the model.

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On my 19-file test folder, 11 files went to the model and the rest were sorted locally. The whole dry-run took about 8.6 seconds in one run.

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