AI File Sorter: Organize Your Files with Local AI and Visual LLMs
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
AI File Sorter is a powerful cross-platform desktop application designed to automate file organization using AI. It leverages local LLMs for privacy-first categorization and can even suggest better filenames for images based on their visual content. This tool helps reduce clutter and improve file discoverability across various storage locations.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
AI File Sorter is a powerful, cross-platform desktop application designed to automate file organization using artificial intelligence. It intelligently categorizes files and can even suggest more descriptive filenames for images by analyzing their visual content. Built with a privacy-first approach, the application primarily uses local LLMs (Large Language Models) like LLaMa and Mistral, ensuring that your files and data never leave your device. It aims to reduce digital clutter, improve consistency, and make your files easier to find for review, archiving, or long-term storage.
Installation
Getting started with AI File Sorter is straightforward. For most users, the easiest way is to use the prebuilt packages or installers available for your operating system.
- Linux: Prebuilt Debian/Ubuntu packages are available, which can be installed using
sudo apt install ./aifilesorter_1.0.0_amd64.debafter installing runtime prerequisites. - macOS: Users can install dependencies via Homebrew and then build from source, or use provided binaries.
- Windows: The recommended method involves using CMake with vcpkg, or the Qt online installer, after setting up Visual Studio 2022.
Detailed instructions for building from source and specific dependencies for various Linux distributions are available in the official GitHub repository.
Examples
Using AI File Sorter involves a simple, guided process:
- Select a Directory: Point the application to the folder or drive you wish to organize.
- Analyze Files: The app scans files, and for images, analyzes their content locally using a visual LLM.
- Review Suggestions: A review dialog presents suggested categories, subcategories, and optional filename changes for images. You can sort, adjust, or approve these suggestions.
- Confirm & Sort: With "Dry run (preview only, do not move files)" enabled, you can inspect planned moves without altering your files. Once satisfied, click "Confirm & Sort!" to execute the organization.
- Undo Last Run: The application saves a persistent undo plan, allowing you to revert the last sorting operation via "Edit ? Undo last run" if needed.
Key features include customizable sorting rules, two categorization modes ("More refined" for detail or "More consistent" for uniformity), and the ability to define category whitelists to constrain model output.
Why Use It
AI File Sorter stands out for several compelling reasons:
- Intelligent Automation: Moves beyond rigid rules, learning your organization patterns over time to provide more consistent and relevant categorization and naming suggestions.
- Privacy-First: By utilizing local LLMs, it ensures that your sensitive files, filenames, images, and metadata are processed entirely on your device, with no data uploaded or telemetry sent.
- Enhanced Discoverability: Reduces clutter and applies meaningful names, making it significantly easier to locate files later.
- Cross-Platform Support: Available on Windows, macOS, and Linux, providing a consistent experience across different environments.
- Flexibility and Control: Offers various categorization modes, category whitelists, and the option to use remote LLMs (like ChatGPT or Gemini) with your own API keys for advanced scenarios, while always requiring your approval before any changes are applied.
- Visual Content Analysis: A unique feature that analyzes image content to suggest descriptive filenames, transforming generic names into something meaningful.
Links
- GitHub Repository: https://github.com/hyperfield/ai-file-sorter
- Download from SourceForge: https://sourceforge.net/projects/ai-file-sorter/files/latest/download
- Get it from Microsoft Store: https://apps.microsoft.com/detail/9npk4dzd6r6s
- Support AI File Sorter (Donate): https://filesorter.app/donate
Related repositories
Similar repositories that may be relevant next.

mcp-gateway: Unifying AI Tool Access with Reduced Context Overhead
August 15, 2026
mcp-gateway is a powerful Rust binary designed to streamline AI agent interaction with diverse tools. It consolidates unlimited MCP servers and REST APIs behind a single, compact endpoint, drastically reducing context token overhead and enabling efficient tool access.

Jan: An Open-Source, Offline ChatGPT Alternative for Your Desktop
August 14, 2026
Jan is a powerful open-source desktop application that provides a 100% offline alternative to ChatGPT. It allows users to download and run various large language models locally, ensuring complete control and privacy over their AI interactions. With support for multiple platforms, Jan offers a robust solution for personal and private AI use.

TurboLLM: Run Local LLMs with Auto-Tuning, Any Engine, and a Polished UI
August 13, 2026
TurboLLM is a powerful, lightweight solution for running local LLM engines, offering auto-tuning for your GPU and a polished web UI. It supports any llama-server compatible binary, including community forks, and provides both OpenAI and Anthropic-compatible APIs. This offline-first tool allows users to maximize performance and flexibility with their local language models.
OpenSandbox: A Secure and Extensible Sandbox Runtime for AI Agents
August 12, 2026
OpenSandbox is a powerful, general-purpose sandbox platform designed for AI applications. It provides secure, fast, and extensible runtime environments, supporting multi-language SDKs and Docker/Kubernetes deployments. This project is ideal for developing and evaluating AI agents in isolated, controlled settings.
Source repository
Open the original repository on GitHub.
13 counted GitHub visits