To address this challenge, we employed Experiment Designer and Hardware Executor agents as the backend of a reaction optimization module within our developed web application, such that users could interface with the reaction optimization hardware system via natural language. This hardware system is a robotic platform capable of performing end-to-end reaction and analysis, and the closedloop reaction optimization was driven by a Bayesian optimization algorithm. Specifically, an automated synthesis equipment (Unchained Big Kahuna) conducts the chemical reactions, which are then analyzed by a high-performance liquid chromatography (HPLC) to provide result feedbacks to the BO for suggesting the next-round reaction candidates. The capability of LLM as an optimizer has been evaluated in recent publications. However, although the LLMs have shown superior performance for optimizing reactions with clear kinetics or prior knowledge, they still fell behind statistical optimization algorithms (e.g., Bayesian optimization) for complex reaction systems .