lastmile-ai/mcp-agent
dottxt-ai/outlines
getomni-ai/zeroxAn embedding is produced by an embedding model that maps an input — a sentence, a document, a snippet of code — to a fixed-length vector of numbers. Inputs with similar meaning land near each other, which turns 'is this similar?' into a fast distance calculation. Embeddings are the foundation of semantic search, recommendations, clustering, and retrieval-augmented generation.
Open-source embedding models trade off dimensionality, speed, language coverage, and domain fit. The right choice depends on your data: a general model works for prose, while code or a specialised domain often benefits from a model trained for it.
