Worked on the weaviate/weaviate-python-client repository to deliver support for the jina-embeddings-v4 model, enabling users to access the latest embedding capabilities for both text and multimodal applications. The approach involved updating Python type aliases, specifically JinaModel and JinaMultimodalModel, to incorporate the new embedding option while maintaining compatibility with previous v2 and v3 models. Configuration files and automated tests were revised to ensure seamless integration and forward compatibility. This work leveraged skills in API integration, full stack development, and Python development, ultimately reducing integration friction and preparing the client for ongoing updates in the embedding model ecosystem.