AIFileNamer 🧠📁

An intelligent, fully autonomous file organisation and renaming desktop application powered by local and cloud AI models.

AIFileNamer reads the content of your files—whether they are text, code, or images—and uses state-of-the-art AI models to automatically generate clean, descriptive filenames and categorise them into logical folder structures.

✨ Features

• Content-Aware Renaming: Analyses file contents (text, code, or images) to generate accurate and highly descriptive filenames.
• Intelligent Folder Sorting: Optionally allows the AI to suggest relative folder structures to automatically sort and categorise your massive directories.
• Bring Your Own AI: Plug-and-play support for major cloud AI providers (OpenAI, Anthropic, Groq, DeepSeek, Google AI Studio, OpenRouter) or 100% private local inference via LM-Studio, Llama.cpp, Jan, GPT4All, and Ollama!
• Multi-Scanner Workspaces: Create multiple independent scanner profiles, each watching a different directory with its own specific AI provider, custom prompts, and rate limits, all running concurrently.
• Infinite Background Syncing: Watch directories effortlessly. Drop new files into your target folder using your OS file explorer, and AIFileNamer instantly picks them up in the UI.
• Fully Autonomous Mode: Enable Auto-Run and watch the app iterate through thousands of files, processing AI requests, organising, and saving everything completely hands-free.
• Extensive File Support: Natively supports extracting text, images, and metadata from Text/Code (.txt, .csv, .md, .json, .js, .ts, .html, .css, etc.), Images (.jpg, .jpeg, .png, .webp, .gif, .avif, .heic, .tiff, .bmp, .psd), and Documents (.pdf, .docx, .doc, .xlsx, .xls, .pptx, .odt, .ods, .odp, .rtf).
• Smart Rate Limiting & Cooling: Fully configurable AI batch limits and processing delays to protect your API credits or let your local GPU cool down between inferences.
• Built-in Error Recovery: Gracefully handles AI timeout or unreadable files with automatic retries and permanent fail states to prevent endless loops.

🚀 Getting Started

Prerequisites

• Node.js (v18+)
• npm
• (Optional) LM-Studio, Llama.cpp, Jan, GPT4All, or Ollama running locally for private, offline AI capabilities.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/AIFileNamer.git
   cd AIFileNamer
   

2. Install dependencies:

   npm install
   

3. Start the application in development mode:

   npm run start
   

Building for Production

To package the app as an executable for your operating system:

npm run build

⚙️ Configuration

1. Open the Config tab inside the app.
2. Select your preferred AI Provider.
3. Enter your API Key (or Local URL for Ollama/LM-Studio).
4. Click Validate & Fetch Models and select the model you wish to use from the dropdown.
5. Customise your AI prompting instructions, batch limits, and processing delays to tailor the app exactly to your workflow.

🛠️ Technology Stack

• Framework: Electron (Desktop Integration) + Svelte (Frontend UI)
• Styling: TailwindCSS
• Build Tool: Vite
• IPC Communication: Secure, context-isolated Electron IPC channels for bridging the sleek Svelte UI with native filesystem operations.

📄 License

This project is licensed under the MIT License.