How I Built SlothFlow: A Local-First AI File Organizer That Cleans Your Mess While You Relax

Description and use

SlothFlow is a local AI file organizer that automatically classifies, renames, and moves documents while keeping all data on the device and offering a safe undo feature.

Problem

Users struggle with disorganized local folders containing PDFs, text, markdown, and other documents, leading to tedious manual renaming and filing, while cloud‑based AI organizers pose privacy risks and subscription costs.

Outcome

SlothFlow achieves local‑first AI file organization, eliminating manual effort, preserving privacy, and providing undo capability, all on standard developer laptops without GPU clusters.

Workflow

• Select a folder or load demo files
• Text extraction via PyMuPDF
• Model inference with local Ollama (Qwen2.5‑1.5B, Gemma 2‑2B, or Llama 3.2‑1B) to produce structured JSON
• Generate organization plan with suggested filenames and target folders
• Preview plan in interactive table (optional inline rename and approval)
• Execute atomic file moves with collision avoidance
• Log actions in SQLite audit trail
• Provide safe undo option

Evidence

SlothFlow is a local-first web application powered by open-weight AI models (Qwen2.5‑1.5B, Gemma 2‑2B, or Llama 3.2‑1B) running on localhost via Ollama.

Source

It inspects documents on your machine, determines their categorization, generates human-readable filenames, and safely organizes them into clean category folders— all while ensuring zero document bytes ever leave your laptop.

Source

Safe Atomic Move & SQLite Audit Log (Instant 1-Click Safe Undo)

Source