InputPurpose

What a text being embedded is for: a document to be indexed, or a query to be run against documents that were indexed.

Several embedding models are trained to embed the two differently, and a mismatch between how texts were indexed and how a query is embedded quietly degrades retrieval. Jina calls the distinction task, Cohere and Voyage call it input_type. A caller always knows which side it is on - indexing or querying - so the request says so, through EmbeddingRequest.purpose, and each provider maps it onto its own parameter.

A provider whose models embed both alike (OpenAI, Ollama) ignores it. A provider author does not need to handle it unless the vendor's API has an equivalent; see the provider guide.

Document is the default of every EmbeddingRequest, so code that does not say which side it is on keeps embedding documents, as it always did.