Worked on the GeeeekExplorer/nano-vllm repository, focusing on improving the reliability of AI model deployment workflows. Addressed a critical issue by fixing the return type of the scheduler’s postprocess method, ensuring type compatibility across integrated components and reducing the risk of type-related errors during deployment. This change streamlined the integration process and contributed to safer, more predictable system behavior. The work involved deep familiarity with Python, as well as expertise in AI model development and machine learning. By resolving this compatibility issue, the developer enhanced the maintainability and robustness of the codebase, supporting smoother collaboration and future feature development.