Wei Chiet focused on backend stability in the BerriAI/litellm repository, addressing streaming error handling within the OpenAIResponsesAPIConfig path. Using Python, he implemented logic to coalesce None error codes into a default string, preventing validation errors during long-running streaming iterations. This approach ensured that error events would consistently return without raising exceptions, improving runtime reliability for LLM streaming. He reinforced these changes with targeted unit tests, validating the transformation and enhancing test coverage. Wei Chiet’s work demonstrated depth in API development and testing, resulting in more maintainable error handling logic and reducing customer-facing issues in production streaming environments.