Haiyi Mei focused on backend stability and error handling for the BerriAI/litellm repository over a two-month period, addressing critical edge cases in token counting and translation workflows. Using Python, Haiyi enhanced the GoogleAIStudioTokenCounter by introducing checks for null or empty input, reducing runtime exceptions and improving downstream reliability. In the translation pipeline, Haiyi resolved failures caused by empty text blocks in system messages, implementing logic to skip these cases and expanding unit test coverage to prevent regressions. The work demonstrated depth in AI and API integration, prioritizing robust error handling and maintainability over feature delivery during this period.