FluxPseudoNegative is an advanced custom node for ComfyUI that converts negative prompts into positive ones. It's designed to enhance prompt engineering for image generation models that don't natively support negative prompts or where using negative prompts significantly increases generation time.

Features

Multiple antonym-finding strategies:
- Custom phrase handling
- WordNet
- NLTK
- Hugging Face Transformers
Comprehensive phrase handling for multi-word concepts
Sentiment analysis for strength adjustment
Concept expansion using word embeddings
Optional ConceptNet integration for expanded antonyms
Multiple processing complexity levels: basic, advanced, expert
Optional LLM integration for unresolved terms or full prompt conversion
User-customizable antonyms and system prompts

Installation

Clone this repository into your ComfyUI custom_nodes directory:

[CODE] git clone https://github.com/yourusername/ComfyUI-FluxPseudoNegativePrompt.git [/CODE]

Install the required dependencies:

[CODE] pip install nltk textblob requests numpy transformers torch [/CODE]

Download the required NLTK data:

[CODE] import nltk nltk.download('averaged_perceptron_tagger') nltk.download('punkt') nltk.download('wordnet') [/CODE]

Usage

In the ComfyUI interface, look for the "Flux Pseudo Negative" node under the "prompt_processing" category.
Connect the node to your workflow:
- Input your negative prompt
- Input a positive prompt to augment
- Adjust the strength parameter (0.0 to 1.0)
- Select the processing complexity
- (Optional) Provide custom antonyms in the format "word:antonym" (one per line)
- (Optional) Enable ConceptNet integration
- (Optional) Enable LLM integration (full or fallback)
- (Optional) Provide a custom system prompt for LLM integration
The node will output:
- A modified positive prompt incorporating the converted negative concepts
- (If LLM integration is enabled) An LLM input string for further processing

Parameters

negative_prompt: The negative prompt to convert
positive_prompt: An optional positive prompt to augment
strength: The strength of the antonym influence (0.0 to 1.0)
complexity: The processing complexity level (basic, advanced, expert)
custom_antonyms: Optional custom antonym mappings
use_conceptnet: Enable ConceptNet integration for concept expansion
use_llm_full: Enable full LLM-based prompt conversion
use_llm_fallback: Enable LLM-based fallback for unresolved terms
custom_system_prompt: Custom system prompt for LLM integration

File Structure

__init__.py: Initializes the node for ComfyUI
FluxPseudoNegative.py: Contains the main FluxPseudoNegativeNode class
flux_utils.py: Contains the PhraseHandler class and strength_map

Customization

You can customize the phrase mappings and strength map by modifying the flux_utils.py file.

Note

This node requires significant computational resources, especially when using advanced NLP features and models. Performance may vary based on your system capabilities and the complexity of the input prompts.

Contributing

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

License

This project is licensed under the MIT License.

Disclaimer

This node uses various third-party APIs and models. Please ensure you comply with their respective terms of use and licensing agreements.