Worked on improving the stability of OpenAI autologging within the mlflow/mlflow repository by addressing a runtime AttributeError related to serialization. The solution involved excluding the run_config attribute from span attributes, which previously led to serialization issues and garbage collection errors when using AsyncHttpxClientWrapper. By refining the autologging mechanism, the contribution enhanced the reliability of MLflow’s backend processes. The work was implemented using Python and leveraged backend development skills, with a focus on ensuring robust integration between MLflow and OpenAI services. This targeted bug fix improved the overall dependability of autologging without introducing new features during the period.