In March 2025, Chibueze Okorie developed a unified service adapter for the Shubhamsaboo/parlant repository, enabling provider-agnostic access to large language models. He integrated LiteLLM as a new service option, architecting the backend to support flexible provider selection and streamline future additions. Using Python and leveraging skills in API integration and full stack development, Chibueze’s work established a scalable foundation for multi-provider AI integrations. This approach reduced vendor lock-in and improved the team’s ability to experiment rapidly with different LLM providers. The depth of the solution lies in its extensibility and its focus on adaptability for evolving business needs.