Shan Cao developed a LiteLLM feature for the google/adk-python repository, focusing on maintaining conversational context during model disruptions by implementing an automatic fallback mechanism. The solution included a model-tracking layer to improve response handling and facilitate debugging, addressing internal issue #2292. Shan collaborated on the project, contributing both to the core fallback logic and a demonstration to validate the approach. The work was delivered in Python, leveraging AI development and machine learning expertise. Over the course of one month, Shan’s contributions provided a robust method for handling interruptions in conversational AI, with clear auditability and collaborative development practices.