How to Integrate OpenAI Embedding API with Zilliz Cloud

In 2018, Zilliz developed Milvus, a vector database designed to enhance search and storage capabilities. The initial focus was on improving the user experience, reliability, performance, and scalability of the platform. As a result, the Milvus community has grown significantly in terms of users, contributors, and stars (nearing 15000). Recently, the community emphasized the need to expand the vector database ecosystem by incorporating visualizations, tools, connectors, etc., with embedding model integrations being one of the most requested features. To address this demand, Zilliz will provide integration examples for Milvus and Zilliz Cloud with open-source or paid embedding models. Additionally, they have launched Towhee, a project that integrates hundreds of open-source models, embedding APIs, and in-house models to create end-to-end search pipelines backed by Milvus or Zilliz Cloud. The company plans to continue its support for the Milvus project while also focusing on integration and partnerships with the broader machine learning ecosystem.

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