In November 2025, Jeejee Lee developed OpenCUA-7B multimodal support for the jeejeelee/vllm repository, focusing on enabling robust multimodal inference. Leveraging deep learning and model development expertise, Jeejee integrated HuggingFace weights, defined custom processors, and registered the new model within the vLLM framework using Python. This work expanded the platform’s compatibility with multimodal models, allowing seamless end-to-end inference in both development and testing environments. Jeejee emphasized code quality and traceability, ensuring reliable deployment and maintainability. The contribution established a foundation for broader multimodal processing capabilities, accelerating the delivery of production-ready AI features without introducing new bugs during the period.