LazySort: The Offline AI File Tidier That Organizes Your Mess For You

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady

What I Built I built LazySort, a background script that watches your messy Downloads folder and automatically categorizes newly saved files into their correct subfolders. It uses a local LLM to read the filename to determine exactly where it should go. It saves me from the tedious chore of manually dragging and dropping files, letting me embrace my inner sloth and be completely lazy about file management.

How I Built It LazySort is built using Python, the watchdog library to monitor folder changes, and Ollama running a lightweight, open-weight model (llama3.2) locally. When a new file is detected, the Python script sends the filename as a prompt to the local Ollama instance, asking it to classify the file into pre-defined categories. Once the AI responds, Python's shutil moves the file automatically. The entire project centers around fast, local, open-source AI inference to handle the routing logic.

Why Does Open Innovation Matter? Open innovation matters for LazySort because file organization deals with highly sensitive personal data—like bank statements, health records, or private photos. A closed API would require me to send my private filenames over the internet to a third-party server, which is a massive privacy risk. By using open-weight models running entirely on my own hardware, this automation works completely offline. It guarantees 100% data privacy and costs absolutely nothing in API fees.

The Lazy Payoff This script saves me about 10-15 minutes of manual sorting every single week. Instead of dreading a cluttered desktop at the end of the week, everything is automatically filed away into "Coursework", "Projects", or "Invoices" folders without me lifting a finger.