PromptEnhancer

What is PromptEnhancer?

PromptEnhancer is Tencent mixed yuan team open source Chinese text to image (Text-to-Image, T2I)Cue word enhancementframework, which aims to improve the comprehension and expression of generative models in Chinese contexts. The tool is able to automatically optimize user-input prompt words, and enable the generative model to more accurately realize the user's intention by adding details, enriching descriptions, and adjusting semantics.

PromptEnhancer is compatible with a wide range of text generation models and supports rapid integration into scenarios such as authoring, education, and intelligent customer service. Users only need to input the original prompt words, and the system can generate optimized augmented prompts and apply them to the target model, thus significantly improving the quality, detail richness and semantic consistency of the generated images.

As an open source tool, PromptEnhancer is available for free and provides simple interfaces for developers and creators to use in various applications, especially suitable for a variety of scenarios, such as content creation, advertisement design, virtual image generation and educational tutoring.

PromptEnhancer's core functionality

• Improve text-to-image modeling accuracy and alignment precision: PromptEnhancer significantly improves the accuracy of text-to-image (T2I) model-generated images and alignment accuracy with user intent by optimizing the text prompts for user inputs, enabling better handling of complex user commands, including attribute bindings, negation commands, and complex relationship descriptions.
• Versatility and Plug and PlayIt does not need to modify the weights of any pre-trained T2I model, and can be used as a general module to adapt to a variety of pre-trained models, such as HunyuanImage, Stable Diffusion, Imagen, etc., to reduce the optimization cost.
• Provision of high-quality benchmarking datasets: The open source contains 6000 Prompts and corresponding multi-dimensional fine labeled high-quality benchmark test dataset, which provides important reference resources for researchers and promotes the interpretability and reproducibility research of prompt optimization techniques.

PromptEnhancer usage scenarios

• advertising design: Quickly generate high-quality advertising posters and promotional materials to improve design efficiency.
• Illustration: Help illustrators generate creative sketches quickly, saving time and effort.
• game design: Generate concept maps of game characters, scenes and props for game developers quickly, speeding up the game development process.
• Social Media Content: Quickly generate engaging social media images and videos to boost the appeal of your content.
• Video Production: Generate high-quality video frames or concept art to assist in video editing and special effects in video content creation.

PromptEnhancer project address

• Project website::https://hunyuan-promptenhancer.github.io/
• GitHub repository::https://github.com/Hunyuan-PromptEnhancer/PromptEnhancer
• HuggingFace Model Library::https://huggingface.co/tencent/HunyuanImage-2.1/tree/main/reprompt
• arXiv Technical Paper::https://www.arxiv.org/pdf/2509.04545

How to use PromptEnhancer?

1. Access platforms: Go to Hunyuan PromptEnhancer Official Website.
2. Enter the prompt: Enter your original cue word in the input box.
3. Select Model: Select the appropriate text generation model as needed.
4. Getting Enhanced Results: Click on the "Enhance" button to get the optimized prompts.
5. Application Generation: Input the optimized cue words into the target model to obtain the generated results.

Recommended Reasons

• Enhancing the quality of generation: Improve the response quality of generated models by optimizing cue words.
• Chinese Optimization: Optimized especially for Chinese contexts to improve performance in Chinese tasks.
• Open source and free: As an open source tool, it is freely available to a wide range of developers.
• Easy to integrate: Provides simple interfaces for easy integration with existing systems.