Developed a unified LoRA Format Adapter for the kvcache-ai/sglang repository, focusing on improving interoperability between multiple LoRA formats and the diffusers framework. The solution automatically detects and normalizes various LoRA formats into a single, consistent structure, streamlining integration for users working with diffusion models. Implemented in Python, the adapter includes conversion utilities and automated regression tests to ensure correctness and maintainability. This work addressed integration friction by simplifying cross-format usage, accelerating experimentation, and supporting broader adoption of multi-format LoRA workflows. Key technical skills applied included data processing, machine learning, Python development, and robust testing practices throughout the project.