OptionaldimensionThe dimension of embedding vectors produced for the index.
Maps the model's input to a field of your documents. Pass
{ text: 'chunk_text' } to embed the chunk_text field of every document
you upsert.
OptionalmetricThe distance metric to use for similarity search. Defaults to the model's preferred metric.
The embedding model to use. Call Inference.listModels to find a model suited to your document text and search queries.
OptionalreadThe read parameters for the embedding model.
OptionalwriteThe write parameters for the embedding model.
The integrated embedding configuration for a new index.
See
Create an index with integrated embedding