Worked on backend development for the nod-ai/SHARK-Platform repository, focusing on stabilizing the SDXL inference workflow. Addressed a critical bug by renaming SDXL-related classes in the Python codebase, ensuring that inference requests and services used the correct SDXL-specific components for Stable Diffusion XL model processing. This change reduced runtime errors and improved the accuracy of request routing within the inference API. The update enhanced code clarity and maintainability, supporting future development and onboarding. Utilized Python to validate the end-to-end SDXL inference path, ultimately preventing misrouting and ensuring compatibility with the evolving requirements of Stable Diffusion XL.