LLMII: Locally Label Metadata and Index Images

LLMII uses a local AI to label metadata and index images. It does not rely on a cloud service or database.

A visual language model runs on your computer and is used to create captions and keywords for images in a directory tree. The generated information is then added to each image file's metadata or to a sidecar file. The images can then be indexed, searched, and organized by by their descriptions using any tool you like that can access the common metadata fields. The files themselves are not bound to any location or tied to any software and the indexer can be run any number of times on the same collection in order to add more metadata or process new images.

The first time you launch the tool you will be presented with a list of AI models to choose from. Once the model weights are downloaded and the dependencies are installed then the tool and all of its components will operate locally.

Features

• Image Analysis: Utilizes a local AI model to generate a list of keywords and a caption for each image
• Metadata Enhancement: Can automatically edit image metadata with generated tags
• Local Processing: All processing is done locally on your machine
• Multi-Format Support: Handles a wide range of image formats, including all major raw camera files
• User-Friendly GUI: Includes a GUI and installer. Relies on Koboldcpp, a single executable, for all AI functionality
• Image View: View images step through them to review the metadata generation after they are processed
• Simple Model Selection: Choose a the state of the art model and it will be automatically downloaded and configured
• Completely Automatic Backend Configuration: The AI backend (KoboldCpp) will be downloaded and configured with optimal settings
• GPU Acceleration: Will use Apple Metal, Nvidia CUDA, or AMD (Vulkan) hardware if available to greatly speed inference
• Cross-Platform: Supports Windows, macOS ARM, and Linux
• Stop and Start Capability: Can stop and start without having to reprocess all the files again
• One or Two Step Processing: Can do keywords and a simple caption in one step, or keywords and a detailed caption in two steps
• Highly Configurable: You are in control of everything
• Multiple Models: You can choose a different model and run it again for additional keywords

Important Information

It is recommended to have a discrete graphics processor in your machine.

This tool operates directly on image file metadata. It will write to one or more of the following fields:

1. MWG:Keyword
2. MWG:Description
3. XMP:Identifier
4. XMP:Status

The "Status" and "Identifier" fields are used to track the processing state of images. The "Description" field is used for the image caption, and "Subject" or "Keyword" fields are used to hold keywords.

The use of the Identifier tag means you can manage your files and add new files, and run the tool as many times as you like without worrying about reprocessing the files that were previously keyworded by the tool.

Installation

Prerequisites

• Python 3.8 or higher

Windows Installation

1. Clone the repository or download the ZIP file and extract it

2. Install Python for Windows

3. Run llmii-windows.bat

macOS Installation (including ARM)

1. Clone the repository or download the ZIP file and extract it

2. Install Python 3.7 or higher if not already installed. You can use Homebrew:

   brew install python
   

3. Install ExifTool:

   brew install exiftool
   

4. Run the script:

   ./llmii.sh
   

5. If KoboldCpp fails to run, open a terminal in the 'resources' folder:

   xattr -cr ./resources/koboldcpp-mac-arm64
   chmod +x ./resources/koboldcpp-mac-arm64
   

Linux Installation

1. Clone the repository or download and extract the ZIP file

2. Install Python 3.8 or higher if not already installed. Use your distribution's package manager, for example on Ubuntu:

   sudo apt-get update
   sudo apt-get install python3 python3-pip
   

3. Install ExifTool. On Ubuntu:

   sudo apt-get install libimage-exiftool-perl
   

4. Run the script:

   ./llmii.sh
   

5. If KoboldCpp fails to run, open a terminal in the 'resources' folder:

   chmod +x ./resources/koboldcpp-linux-x64
   

Usage

1. Launch the LLMII GUI:

   • On Windows: Run llmii-windows.bat
   • On macOS/Linux: Run ./llmii.sh

2. Ensure KoboldCPP is running. Wait until you see the following message in the KoboldCPP window:

   Please connect to custom endpoint at http://localhost:5001
   

3. Configure the indexing settings in the GUI

4. Click "Run Image Indexer" to start the process

5. Monitor the progress in the output area of the GUI.

Languages

It is sometimes possible to get keywords or captions in a language besides English. You will need to modify the instruction and uncheck some keyword options. To do this:

1. In the GUI, click on "Settings" and then "Edit Instructions":

   • Replace ENGLISH in the instructions with the name of a different language

2. In Keyword Corrections:

   • Uncheck "Depluralize keywords"
   • Uncheck "Only Latin characters"

Settings

Press the HELP button in the settings dialog.

More Information and Troubleshooting

Consult the wiki for detailed information.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the GPLv3 License - see the LICENSE file for details.

Acknowledgements

• ExifTool for metadata manipulation
• KoboldCPP for local AI processing and for the GPU information logic
• PyQt6 for the GUI framework
• Fix Busted JSON and Json Repair for help with mangled JSON parsing