Create Index
kendra_create_index | R Documentation |
Creates an Amazon Kendra index¶
Description¶
Creates 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 describe_index
. 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
batch_put_document
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.
Usage¶
kendra_create_index(Name, Edition, RoleArn,
ServerSideEncryptionConfiguration, Description, ClientToken, Tags,
UserTokenConfigurations, UserContextPolicy,
UserGroupResolutionConfiguration)
Arguments¶
Name |
[required] A name for the index. |
Edition |
The Amazon Kendra edition to use for the index. Choose
The For more information on quota limits for Gen AI Enterprise Edition, Enterprise Edition, and Developer Edition indices, see Quotas. |
RoleArn |
[required] 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 |
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 |
A description for the index. |
ClientToken |
A token that you provide to identify the request to create an
index. Multiple calls to the |
Tags |
A list of key-value pairs that identify or categorize the index. You can also use tags to help control access to the index. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @. |
UserTokenConfigurations |
The user token configuration. If you're using an Amazon Kendra Gen AI Enterprise Edition index and
you try to use |
UserContextPolicy |
The user context policy. If you're using an Amazon Kendra Gen AI Enterprise Edition index, you
can only use 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_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 |
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,
|
Value¶
A list with the following syntax:
list(
Id = "string"
)
Request syntax¶
svc$create_index(
Name = "string",
Edition = "DEVELOPER_EDITION"|"ENTERPRISE_EDITION"|"GEN_AI_ENTERPRISE_EDITION",
RoleArn = "string",
ServerSideEncryptionConfiguration = list(
KmsKeyId = "string"
),
Description = "string",
ClientToken = "string",
Tags = list(
list(
Key = "string",
Value = "string"
)
),
UserTokenConfigurations = list(
list(
JwtTokenTypeConfiguration = list(
KeyLocation = "URL"|"SECRET_MANAGER",
URL = "string",
SecretManagerArn = "string",
UserNameAttributeField = "string",
GroupAttributeField = "string",
Issuer = "string",
ClaimRegex = "string"
),
JsonTokenTypeConfiguration = list(
UserNameAttributeField = "string",
GroupAttributeField = "string"
)
)
),
UserContextPolicy = "ATTRIBUTE_FILTER"|"USER_TOKEN",
UserGroupResolutionConfiguration = list(
UserGroupResolutionMode = "AWS_SSO"|"NONE"
)
)