Values.CreateIndexRequestSourceCreates an Amazon Kendra index. Index creation is an asynchronous API. To determine if index creation has completed, check the Status field returned from a call to DescribeIndex. The Status field is set to ACTIVE when the index is ready to use. Once the index is active, you can index your documents using the BatchPutDocument API or using one of the supported data sources. For an example of creating an index and data source using the Python SDK, see Getting started with Python SDK. For an example of creating an index and data source using the Java SDK, see Getting started with Java SDK.
type nonrec t = {name : IndexName.t;A name for the index.
*)edition : IndexEdition.t option;The Amazon Kendra edition to use for the index. Choose DEVELOPER_EDITION for indexes intended for development, testing, or proof of concept. Use ENTERPRISE_EDITION for production. Use GEN_AI_ENTERPRISE_EDITION for creating generative AI applications. Once you set the edition for an index, it can't be changed. The Edition parameter is optional. If you don't supply a value, the default is ENTERPRISE_EDITION. For more information on quota limits for Gen AI Enterprise Edition, Enterprise Edition, and Developer Edition indices, see Quotas.
*)roleArn : RoleArn.t;The Amazon Resource Name (ARN) of an IAM role with permission to access your Amazon CloudWatch logs and metrics. For more information, see IAM access roles for Amazon Kendra.
*)serverSideEncryptionConfiguration : ServerSideEncryptionConfiguration.t option;The identifier of the KMS customer managed key (CMK) that's used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn't support asymmetric CMKs.
*)description : Description.t option;A description for the index.
*)clientToken : ClientTokenName.t option;A token that you provide to identify the request to create an index. Multiple calls to the CreateIndex API with the same client token will create only one index.
*)userTokenConfigurations : UserTokenConfigurationList.t option;The user token configuration. If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use UserTokenConfigurations to configure user context policy, Amazon Kendra returns a ValidationException error.
*)userContextPolicy : UserContextPolicy.t option;The user context policy. If you're using an Amazon Kendra Gen AI Enterprise Edition index, you can only use ATTRIBUTE_FILTER to filter search results by user context. If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use USER_TOKEN to configure user context policy, Amazon Kendra returns a ValidationException error. ATTRIBUTE_FILTER All indexed content is searchable and displayable for all users. If you want to filter search results on user context, you can use the attribute filters of _user_id and _group_ids or you can provide user and group information in UserContext. USER_TOKEN Enables token-based user access control to filter search results on user context. All documents with no access control and all documents accessible to the user will be searchable and displayable.
*)userGroupResolutionConfiguration : UserGroupResolutionConfiguration.t option;Gets users and groups from IAM Identity Center identity source. To configure this, see UserGroupResolutionConfiguration. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents. If you're using an Amazon Kendra Gen AI Enterprise Edition index, UserGroupResolutionConfiguration isn't supported.
*)}val make :
?edition:??? ->
?serverSideEncryptionConfiguration:??? ->
?description:??? ->
?clientToken:??? ->
?tags:??? ->
?userTokenConfigurations:??? ->
?userContextPolicy:??? ->
?userGroupResolutionConfiguration:??? ->
name:IndexName.t ->
roleArn:RoleArn.t ->
unit ->
tval to_value :
t ->
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(string * [> `Enum of string | `String of Url.t ]) list ])
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list
| `String of IndexName.t
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(string * [> `Enum of string | `String of KmsKeyId.t ]) list ])
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