Developed a privacy-focused feature for the pydantic/pydantic-ai repository, introducing an openai_store setting that allows users to control whether OpenAI API outputs are stored. This addition enables organizations to manage data retention and align with privacy and compliance requirements. The implementation involved updating model settings to ensure consistent behavior across configurations and adding automated unit tests to validate the new functionality and prevent regressions. Leveraging Python for API development and data privacy management, the work enhanced data governance by making OpenAI response storage configurable, thereby supporting enterprise needs for compliance and reducing risk associated with sensitive data handling.