AI
Embedding model
How Embedding model connects to the rest of the stack: what it depends on, what depends on it, and what it is commonly deployed alongside.
Concepts it implements
Context window
The fixed number of tokens a model can attend to on one request, shared between the system prompt, tools, retrieved documents, history and the answer itself.
EmbeddingA fixed-length vector that represents the meaning of a piece of text, image or other input, positioned so that similar items are nearby in the vector space.
Where Embedding model sits
How this component relates to the rest of the stack. Items without a link are not covered here yet.