Lee developed two core features over two months, focusing on multimodal model integration and document processing. For the ROCm/vllm repository, Lee added H2OVL-Mississippi multimodal model support, enabling both image and text processing within inference pipelines. This involved implementing image-input handling and comprehensive testing to ensure reliability and compatibility with various input formats. In the tensorlakeai/tensorlake repository, Lee delivered new parsing options for the Document AI SDK, introducing signature detection, skew correction, and selective OCR skipping to improve document analysis accuracy. The work demonstrated depth in Python, machine learning, and SDK development, with a strong emphasis on robust integration.