ComfyUI Vision LLM Analyzer Node

ComfyUI Vision LLM Analyzer Node

This repository contains a powerful and versatile custom node for ComfyUI that seamlessly integrates with OpenAI-compatible Large Language Models (LLMs), including multimodal (vision-enabled) models like GPT-4o.

This single node allows you to perform both text generation and image analysis, making it an essential tool for advanced prompt engineering and creative automation.

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✨ Features

• Dual Functionality: Operates as a standard text-generation LLM node or as a vision-enabled image analyzer.
• Optional Image Input: The image input is optional. If an image is provided, the node performs multimodal analysis. If not, it functions as a text-only LLM.
• Frontend Configuration: Easily configure the following directly on the node:
  • API Key: Securely input your API key.
  • Base URL: Customize the API endpoint to use services other than OpenAI (e.g., local LLMs, other providers).
  • System Role: Define the behavior and personality of the AI model.
  • User Prompt: Provide the main instruction or question.
  • Model Selection: Specify the model to use (e.g., gpt-4o, gpt-3.5-turbo).
• Seamless Integration: The text output can be connected to any other ComfyUI node that accepts a string input, such as a prompt for a text-to-image sampler.

⚙️ Installation

1. Navigate to the custom_nodes directory in your ComfyUI installation folder:

   cd ComfyUI/custom_nodes/
   

2. Clone this GitHub repository into the custom_nodes directory:

   git clone https://github.com/Aero-Ex/ComfyUI-Vision-LLM-Analyzer.git
   

3. Install the required dependencies by navigating into the new directory and running pip:

   cd ComfyUI-Vision-LLM-Analyzer/
   pip install -r requirements.txt
   

4. Restart ComfyUI.

The "Vision LLM Analyzer" node will now be available under the "LLM" category when you right-click on the canvas.

🚀 How to Use

Once installed, you can add the "Vision LLM Analyzer" node to your workflow.

Use Case 1: Image Analysis (Multimodal)

1. Connect an Image output from another node (e.g., "Load Image") to the image input of the Vision LLM Analyzer node.
2. Fill in your api_key, and confirm the base_url is correct for your provider.
3. Set the role_prompt to guide the AI's persona (e.g., "You are a master art critic.").
4. Write your user_prompt to ask a question about the image (e.g., "Describe the artistic style and mood of this image.").
5. Connect the STRING output of this node to another node's text input to use the generated description.

Use Case 2: Text Generation (Standard LLM)

1. Leave the image input disconnected.
2. Fill in your api_key and base_url.
3. Set the role_prompt (e.g., "You are a creative writer.").
4. Write your user_prompt with the text you want the LLM to process (e.g., "Generate three fantasy character concepts with unique backstories.").
5. Use the STRING output for your other nodes.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.

📄 License

This project is licensed under the MIT License.