An embedding function that utilizes the OpenAI API to compute vector embeddings, commonly used with vector databases.

A pre-trained model used for extracting embeddings from content like PDFs, videos, and transcripts, which are then stored in vector databases for faster search.

A curated awesome list compiling resources, tools, vector databases, and research relevant to vector search and storage. Serves as a meta-resource for exploring the vector database ecosystem.

A curated collection of libraries, services, and research papers focused on vector search, including vector database technologies and related resources.

Examples and resources for Weaviate, a popular open-source vector database optimized for storing and searching vector embeddings at scale.

A curated directory of resources, tools, tutorials, and libraries dedicated to vector databases, focusing on efficient data retrieval, similarity search, and machine learning applications.