I Built slothd: A Local-First, Offline-Capable AI Daemon That Patiently Organizes Your Messy Workspace

Описание и применение

Разработчик создал локальный демон slothd, который автоматически организует файлы в рабочем пространстве без подключения к интернету, используя модели Gemma 3 и TabPFN, а также журнал SQLite для отката изменений.

Задача

Users spend time manually organizing cluttered workspaces, risking privacy by uploading sensitive files to cloud AI services.

Результат

In under a second, the demo fixture of 10 files was scanned, 2 clutter anomalies flagged, 1 duplicate set detected, and no cloud API calls were made, demonstrating 100% offline operation.

Рабочий процесс

• Detect keyboard/mouse inactivity
• Scan target directory
• Extract 7 tabular signals
• Run Prior Labs TabPFN triage
• Flag anomalies
• Run Gemma 3 via Ollama for document understanding
• Generate organization plan
• Dry‑run preview
• Approve plan
• Move files
• Index in Tiger Data pgvector or local SQLite
• Provide semantic search
• Log actions in SQLite WAL
• Enable 1‑click rollback

Доказательства

I built **slothd**, a local-first, offline-capable AI file organizer designed around the philosophy of **"Slow and Steady"**

Источник

Uses native OS APIs to measure keyboard and mouse inactivity. It sleeps while you work and only activates when you step away.

Источник

Fast metadata triage (1ms via local 7-signal engine, ~20ms via **Prior Labs TabPFN**) flags anomalies before invoking heavier models.

Источник

Uses **Gemma 3** running locally in **Ollama** with strict Pydantic JSON schemas to read PDFs, invoices, and images.

Источник

Every run is a dry‑run by default. Every approved move is written to an SQLite WAL log with a unique batch ID. If you dislike what it did, slothd undo restores every file to its exact original path.

Источник

The entire core workflow—idle detection, filesystem scanning, tabular metadata triage, Gemma 3 document understanding via local Ollama, SQLite WAL manifests, and 1‑click rollback—executes **100% locally on your machine with zero internet calls.

Источник

Anyone can clone and run the scan immediately: git clone https://github.com/JaniDhruv/slothd.git uv run slothd scan test_workspace/messy_inbox

Источник