Worked on the jupyterlab/jupyter-ai repository to enhance the reliability of AI inference workflows by addressing a critical JSON serialization issue in the Jupyter AI callback for Ollama models. Developed a robust utility in Python to ensure that model data and agent message metadata are consistently converted to JSON-serializable formats, preventing downstream errors and improving the stability of API integrations. Focused on backend development and error handling, the solution introduced metadata validation to the callback pipeline, ensuring that only serializable data is processed. This targeted fix strengthened the robustness of metadata handling and contributed to more dependable AI integration workflows.