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Updates SDK to v2.1631.0
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‎.changes/2.1631.0.json

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[
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{
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"type": "feature",
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"category": "ACM",
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"description": "add v2 smoke tests and smithy smokeTests trait for SDK testing."
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},
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{
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"type": "feature",
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"category": "BedrockAgent",
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"description": "With this release, Knowledge bases for Bedrock adds support for Titan Text Embedding v2."
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},
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{
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"type": "feature",
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"category": "BedrockRuntime",
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"description": "This release adds Converse and ConverseStream APIs to Bedrock Runtime"
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},
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{
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"type": "feature",
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"category": "CloudTrail",
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"description": "CloudTrail Lake returns PartitionKeys in the GetEventDataStore API response. Events are grouped into partitions based on these keys for better query performance. For example, the calendarday key groups events by day, while combining the calendarday key with the hour key groups them by day and hour."
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},
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{
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"type": "feature",
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"category": "Connect",
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"description": "Adding associatedQueueIds as a SearchCriteria and response field to the SearchRoutingProfiles API"
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},
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{
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"type": "feature",
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"category": "EMRServerless",
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"description": "The release adds support for spark structured streaming."
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},
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{
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"type": "feature",
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"category": "SageMaker",
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"description": "Adds Model Card information as a new component to Model Package. Autopilot launches algorithm selection for TimeSeries modality to generate AutoML candidates per algorithm."
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}
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]

‎CHANGELOG.md

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# Changelog for AWS SDK for JavaScript
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<!--LATEST=2.1630.0-->
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<!--LATEST=2.1631.0-->
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<!--ENTRYINSERT-->
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## 2.1631.0
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* feature: ACM: add v2 smoke tests and smithy smokeTests trait for SDK testing.
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* feature: BedrockAgent: With this release, Knowledge bases for Bedrock adds support for Titan Text Embedding v2.
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* feature: BedrockRuntime: This release adds Converse and ConverseStream APIs to Bedrock Runtime
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* feature: CloudTrail: CloudTrail Lake returns PartitionKeys in the GetEventDataStore API response. Events are grouped into partitions based on these keys for better query performance. For example, the calendarday key groups events by day, while combining the calendarday key with the hour key groups them by day and hour.
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* feature: Connect: Adding associatedQueueIds as a SearchCriteria and response field to the SearchRoutingProfiles API
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* feature: EMRServerless: The release adds support for spark structured streaming.
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* feature: SageMaker: Adds Model Card information as a new component to Model Package. Autopilot launches algorithm selection for TimeSeries modality to generate AutoML candidates per algorithm.
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## 2.1630.0
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* feature: Athena: Throwing validation errors on CreateNotebook with Name containing `/`,`:`,`\`
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* feature: CodeBuild: AWS CodeBuild now supports manually creating GitHub webhooks

‎README.md

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To use the SDK in the browser, simply add the following script tag to your
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HTML pages:
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<script src="https://sdk.amazonaws.com/js/aws-sdk-2.1630.0.min.js"></script>
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<script src="https://sdk.amazonaws.com/js/aws-sdk-2.1631.0.min.js"></script>
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You can also build a custom browser SDK with your specified set of AWS services.
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This can allow you to reduce the SDK's size, specify different API versions of

‎apis/acm-2015-12-08.min.json

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"endpointPrefix": "acm",
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"jsonVersion": "1.1",
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"protocol": "json",
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"protocols": [
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"json"
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],
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"serviceAbbreviation": "ACM",
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"serviceFullName": "AWS Certificate Manager",
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"serviceId": "ACM",

‎apis/acm-2015-12-08.normal.json

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"endpointPrefix": "acm",
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"jsonVersion": "1.1",
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"protocol": "json",
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"protocols": [
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"json"
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],
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"serviceAbbreviation": "ACM",
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"serviceFullName": "AWS Certificate Manager",
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"serviceId": "ACM",

‎apis/bedrock-agent-2023-06-05.min.json

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"name": {},
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"roleArn": {},
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"storageConfiguration": {
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"shape": "S2w"
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"shape": "S2z"
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},
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"tags": {
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"shape": "S10"
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],
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"members": {
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"knowledgeBase": {
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"shape": "S3q"
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"shape": "S3t"
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}
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}
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},
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],
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"members": {
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"ingestionJob": {
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"shape": "S4n"
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"shape": "S4q"
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}
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}
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}
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],
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"members": {
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"knowledgeBase": {
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"shape": "S3q"
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"shape": "S3t"
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}
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}
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}
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"shape": "S9"
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},
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"statistics": {
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"shape": "S4o"
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"shape": "S4r"
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"status": {},
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"updatedAt": {
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],
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"members": {
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"ingestionJob": {
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"shape": "S4n"
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"shape": "S4q"
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}
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}
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},
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"name": {},
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"roleArn": {},
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"storageConfiguration": {
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"shape": "S2z"
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}
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},
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],
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"members": {
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"knowledgeBase": {
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"shape": "S3q"
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"shape": "S3t"
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}
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}
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},
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"embeddingModelArn"
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],
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"members": {
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"embeddingModelArn": {}
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"embeddingModelArn": {},
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"embeddingModelConfiguration": {
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"type": "structure",
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"members": {
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"bedrockEmbeddingModelConfiguration": {
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"type": "structure",
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"members": {
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"dimensions": {
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"type": "integer"
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}
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}
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}
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}
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}
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}
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}
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}
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},
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"S2w": {
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"S2z": {
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"type": "structure",
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"required": [
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"type"
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"type": {}
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"S3q": {
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"S3t": {
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"type": "structure",
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"required": [
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"createdAt",
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"roleArn": {},
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"status": {},
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"storageConfiguration": {
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"shape": "S2w"
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"shape": "S2z"
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"updatedAt": {
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"shape": "S9"
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}
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}
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"S4n": {
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"S4q": {
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"type": "structure",
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"required": [
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"dataSourceId",
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"shape": "S9"
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"statistics": {
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"status": {},
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"shape": "S9"
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"S4r": {
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"type": "structure",
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"members": {
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"numberOfDocumentsDeleted": {

‎apis/bedrock-agent-2023-06-05.normal.json

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"min": 20,
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"pattern": "^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:provisioned-model/[a-z0-9]{12})))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)$"
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},
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"BedrockEmbeddingModelConfiguration": {
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"type": "structure",
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"members": {
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"dimensions": {
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"shape": "Dimensions",
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"documentation": "<p>The dimensions details for the vector configuration used on the Bedrock embeddings model.</p>"
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}
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},
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"documentation": "<p>The vector configuration details for the Bedrock embeddings model.</p>"
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},
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"Boolean": {
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"type": "boolean",
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"box": true
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"max": 200,
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"min": 1
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},
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"Dimensions": {
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"type": "integer",
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"box": true,
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"max": 4096,
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"min": 0
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},
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"DisassociateAgentKnowledgeBaseRequest": {
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"type": "structure",
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"required": [
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"min": 5,
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"pattern": "^DRAFT$"
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},
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"EmbeddingModelConfiguration": {
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"type": "structure",
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"members": {
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"bedrockEmbeddingModelConfiguration": {
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"shape": "BedrockEmbeddingModelConfiguration",
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"documentation": "<p>The vector configuration details on the Bedrock embeddings model.</p>"
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}
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},
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"documentation": "<p>The configuration details for the embeddings model.</p>"
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},
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"FailureReason": {
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"type": "string",
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"max": 2048,
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"embeddingModelArn": {
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"shape": "BedrockEmbeddingModelArn",
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"documentation": "<p>The Amazon Resource Name (ARN) of the model used to create vector embeddings for the knowledge base.</p>"
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},
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"embeddingModelConfiguration": {
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"shape": "EmbeddingModelConfiguration",
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"documentation": "<p>The embeddings model configuration details for the vector model used in Knowledge Base.</p>"
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}
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},
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"documentation": "<p>Contains details about the model used to create vector embeddings for the knowledge base.</p>"

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