During this period, work centered on enhancing the PaddlePaddle/PaddleFormers repository by introducing an example configuration and provider for the GLM-4.5 model within PaddleFleet. This addition aimed to streamline large language model workflows, supporting scalable training and evaluation processes. The approach involved developing a clear, reusable configuration template that facilitates GLM-4.5 deployments, aligning with the project’s roadmap and maintaining strong version-control practices. Utilizing Python and leveraging deep learning and model training expertise, the contribution improved the framework’s readiness for advanced LLM scenarios. The work demonstrated a focus on maintainability and integration, addressing evolving needs in machine learning infrastructure.