Guangtong Bai developed scalable Run:AI model streaming support for vLLM within the ai-dynamo/dynamo repository. He integrated the Run:AI model streamer, updating installation scripts and project configuration to ensure all necessary dependencies were included for seamless deployment. Using Python and shell scripting, Guangtong validated the end-to-end streaming workflow in a development environment, preparing the infrastructure for production readiness. His work focused on containerization and DevOps practices, enabling robust, real-time model streaming across deployments. This feature accelerates experimentation and enhances scalability for model workloads, demonstrating depth in dependency management and deployment configuration without addressing critical bug fixes during the period.