ComfyUI Extension: SaltAI_Language_Toolkit

Authored by get-salt-AI

Created

Updated

320 stars

The project integrates the Retrieval Augmented Generation (RAG) tool a/Llama-Index, a/Microsoft's AutoGen, and a/LlaVA-Next with ComfyUI's adaptable node interface, enhancing the functionality and user experience of the platform.

Custom Nodes (0)

    README

    SaltAI Language Toolkit

    The project integrates the Retrieval Augmented Generation (RAG) tool Llama-Index, Microsoft's AutoGen, and LlaVA-Next with ComfyUI's adaptable node interface, enhancing the functionality and user experience of the platform.

    šŸ”„ May 9, 2024: Added agents, more information can be found here.

    Installation Instructions

    Using Git and Pip

    Follow these steps to set up the environment:

    1. Set up a virtual environment as needed.

    2. Navigate to ComfyUI/custom_nodes.

    3. Clone the repository: git clone https://github.com/get-salt-AI/SaltAI_LlamaIndex

    4. Change to the cloned directory: cd SaltAI_Llama-index

    5. Install dependencies:

      5.a Python venv:

      • pip install -r requirements.txt

      5.b ComfyUI Portable:

      • path\to\ComfyUI\python_embeded\python.exe -m pip install -r requirements.txt

    ComfyUI Manager

    1. Have ComfyUI-Manager installed.
    2. Open up Manager within ComfyUI and search for the nodepack "SaltAI_LlamaIndex"
    3. Install
    4. Restart the server.
    5. Ctrl+F5 Hard refresh the browser.

    Installation Note:

    You may need to update your environments packaging, wheels, and setuptools for newer Transformers and LlaVA-Next models.

    • pip install --upgrade packaging setuptools wheel Or
    • path\to\ComfyUI\python_embeded\python.exe -m pip install --upgrade packaging setuptools wheel

    Examples

    Example workflows and images can be found in the Examples Section folder.

    • Example_agents.json - shows you how to create conversible agents, with various examples of how they could be setup.
    • Example_groq_search.json - shows you how to search with a Groq LLM model, featuring Tavily Research node.
    • Example_SERP_search.json - shows you how to search with Scale SERP, and also demonstrates how to use different models with same setup.
    • Example_search_to_json.json - shows you how to take search results, and convert them to JSON output which could be fed to another system for use.

    Troubleshooting

    If you encounter issues due to package conflicts, ensure your virtual environment is configured correctly.

    Acquiring Models

    You can install and use any GGUF files loaded into your ComfyUI/custom_nodes/models/llm folder.

    Here is probably the world's largest repository of those:

    Hugging Face LLM Category

    Documentation and Contributions

    Detailed documentation and guidelines for contributing to the project will be provided soon.

    You can find out existing documentation at https://docs.getsalt.ai/

    License

    The project is open-source under the MIT license.