A custom node for ComfyUI that facilitates the integration of OpenAI-compatible Large Language Models (LLMs) APIs, this tool supports both text-based and multimodal interactions, allowing users to process text and images simultaneously. It is designed to work with OpenAI's GPT models, as well as local models like Ollama and LLaVA, ensuring flexibility in accessing various AI capabilities.
- Supports multi-line prompts and optional image inputs for enhanced interaction.
- Configurable to work with multiple API endpoints, including OpenAI and local services.
- Provides robust error handling and automatic image encoding for seamless integration.
Context
This custom node serves as a bridge between ComfyUI and OpenAI-compatible LLM APIs, enabling users to utilize advanced language models for both text and image processing tasks. Its main purpose is to enhance the capability of ComfyUI by allowing multimodal interactions, which can significantly improve the quality of generated content and analysis.
Key Features & Benefits
The tool offers a multi-line prompt input feature, allowing users to enter complex queries easily. It supports image inputs for multimodal models, which is crucial for applications that require both visual and textual analysis. Furthermore, the node can connect to various API endpoints, providing flexibility to users who may be utilizing local or cloud-based models.
Advanced Functionalities
One of the specialized capabilities of this node is its automatic image encoding, which converts images into a base64 format for compatibility with API requests. This feature simplifies the process of sending images to the LLMs, ensuring that users do not need to manually handle image formatting. Additionally, the node includes detailed control over generation parameters, such as maximum tokens and temperature, allowing for tailored responses.
Practical Benefits
By integrating this node into their workflows, users can significantly enhance their control over the generation process, improving the quality and relevance of outputs. The ability to handle both text and images in a single interaction streamlines workflows, making it easier to conduct complex analyses and generate creative content efficiently. The comprehensive error handling further ensures that users can troubleshoot issues effectively, maintaining a smooth operational flow.
Credits/Acknowledgments
This project is developed under the MIT License, with contributions from various authors and the open-source community. Users are encouraged to refer to the GitHub repository for more information on contributors and to engage in discussions or report issues.