Developed Laguna model support within the jeejeelee/vllm repository, focusing on integrating dflash functionality and aligning the new model with existing VLLM interfaces. This work expanded the framework’s compatibility, enabling broader model coverage and laying the groundwork for production-ready deployments. The technical approach involved Python-based model interface adapters and careful adherence to VLLM’s architectural contracts, ensuring seamless interoperability. Collaborative development practices were demonstrated through co-authored commits and integration-focused engineering. No separate bug fixes were required beyond the integration effort, reflecting a targeted and robust implementation. Skills applied included deep learning, machine learning, and model development using Python within the VLLM framework.