The public cloud to host the index on: aws, gcp, or azure.
OptionaldeletionWhether to enable deletion protection. Defaults to disabled.
The embedding model and the document field it reads.
The name of the index to create. Must be unique within the project.
OptionalreadThe native nested or deprecated flat read capacity configuration for the index. Omit for on-demand capacity.
The cloud region to create the index in, for example us-east-1.
OptionalschemaOptionalsuppressWhen true, returns undefined instead of throwing if an index with this
name already exists. Otherwise creation always returns an index model,
regardless of waitUntilReady.
OptionaltagsCustom user tags added to an index, at most 20 per index. Keys must be 80 characters or less and alphanumeric, '_', or '-'. Values must be 120 characters or less and consist of printable ASCII characters or spaces. To unset a key, set the value to be an empty string. null in responses when the index has no tags.
OptionaltimeoutMaximum time in milliseconds to wait for the index to become ready when
waitUntilReady is true. Omit to poll indefinitely.
Throws Errors.PineconeTimeoutError if the deadline is exceeded.
OptionalwaitWhen true, polls until the index is ready before returning.
Options for creating an index with an integrated embedding model.
The
embedsettings select the model and document field to embed for you. For full control over schema composition — combining a dense or sparse vector field with full-text search, for example — use Indexes.create directly.See
Create an index with integrated embedding