Worked on the xinnan-tech/xiaozhi-esp32-server repository, delivering a feature that normalizes dialogue messages to ensure each includes a content field. This approach improved the robustness of dialogue processing within the LLMProvider by reducing downstream errors and simplifying maintenance. The implementation involved updating the OpenAI integration logic in Python to handle normalized messages, addressing edge-case failures in dialogue handling. Focused on backend development and API integration, the work emphasized input validation and codebase quality improvements. Over the course of one month, the contribution centered on enhancing reliability in dialogue management, with no major bugs reported or fixed during this period.