I work at NSFW Coders, and currently, I’m developing a Candy AI Clone API that focuses on enhancing image generation features through adaptive AI models. The main objective is to combine conversational understanding with text-to-image generation to create a more natural and personalized experience.
During the process, I’ve been experimenting with different diffusion models and prompt optimization techniques to improve image accuracy and reduce response time. We’re also exploring how contextual dialogue history can influence image outputs for more human-like consistency.
I’d like to hear from other developers working on similar AI systems — which frameworks or optimization tricks have helped you improve efficiency and realism in image generation?