During August, Boyu Zhang focused on stabilizing multi-modal inference in the modelscope/ms-swift repository by addressing a critical bug in vLLM inference. He identified and resolved an issue where multi_modal_data was incorrectly constructed when multiple media inputs were present, which previously led to data-passing errors and unreliable inference results. Using Python and leveraging his expertise in LLM inference and multi-modal processing, Boyu delivered a targeted fix that improved the reliability of mixed media workflows. His work demonstrated thorough debugging and a rapid development cycle, resulting in reduced customer-facing defects and a more robust multi-modal pipeline within the project’s codebase.