Andy worked on enhancing embedding response handling in the BerriAI/litellm repository, focusing on integrating support for Cohere v4 embeddings. He implemented logic in Python to parse embedding responses structured as dictionaries keyed by type, updating the backend transformation process to accommodate this new format. Andy also developed and expanded unit tests to validate the updated response handling, ensuring compatibility with external API changes and reducing potential runtime errors. His work centered on robust API integration and backend development, providing a maintainable foundation for future embedding improvements and supporting ongoing data-quality and model-integration objectives within the project’s evolving requirements.