Local-File-Organizer is a local-first file classification system that uses on-device machine learning models to categorize documents and media into structured directories. It functions as an automated file classifier and asset manager that leverages local inference to sort files based on content, meaning, and metadata.
The project emphasizes privacy by performing all data processing and analysis on the local device, eliminating the need to send sensitive files to external cloud services. It utilizes local models to analyze text and image content to generate descriptive filenames and thematic folder hierarchies.
Beyond AI-driven organization, the system includes rule-based sorting utilities for grouping files by extension or chronological timestamps. It also provides a simulation feature that allows users to preview resulting directory structure changes before applying them to the filesystem.