createKnowledgeBase method

Future<CreateKnowledgeBaseResponse> createKnowledgeBase({ required KnowledgeBaseConfiguration knowledgeBaseConfiguration, required String name, required String roleArn, String? clientToken, String? description, StorageConfiguration? storageConfiguration, Map<String, String>? tags, })

Creates a knowledge base. A knowledge base contains your data sources so that Large Language Models (LLMs) can use your data. To create a knowledge base, you must first set up your data sources and configure a supported vector store. For more information, see Set up a knowledge base.

• Provide the name and an optional description.
• Provide the Amazon Resource Name (ARN) with permissions to create a knowledge base in the roleArn field.
• Provide the embedding model to use in the embeddingModelArn field in the knowledgeBaseConfiguration object.
• Provide the configuration for your vector store in the storageConfiguration object.
  • For an Amazon OpenSearch Service database, use the opensearchServerlessConfiguration object. For more information, see Create a vector store in Amazon OpenSearch Service.
  • For an Amazon Aurora database, use the RdsConfiguration object. For more information, see Create a vector store in Amazon Aurora.
  • For a Pinecone database, use the pineconeConfiguration object. For more information, see Create a vector store in Pinecone.
  • For a Redis Enterprise Cloud database, use the redisEnterpriseCloudConfiguration object. For more information, see Create a vector store in Redis Enterprise Cloud.

May throw AccessDeniedException. May throw ConflictException. May throw InternalServerException. May throw ServiceQuotaExceededException. May throw ThrottlingException. May throw ValidationException.

Parameter knowledgeBaseConfiguration : Contains details about the embeddings model used for the knowledge base.

Parameter name : A name for the knowledge base.

Parameter roleArn : The Amazon Resource Name (ARN) of the IAM role with permissions to invoke API operations on the knowledge base.

Parameter clientToken : A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency.

Parameter description : A description of the knowledge base.

Parameter storageConfiguration : Contains details about the configuration of the vector database used for the knowledge base.

Parameter tags : Specify the key-value pairs for the tags that you want to attach to your knowledge base in this object.

Implementation

Future<CreateKnowledgeBaseResponse> createKnowledgeBase({
  required KnowledgeBaseConfiguration knowledgeBaseConfiguration,
  required String name,
  required String roleArn,
  String? clientToken,
  String? description,
  StorageConfiguration? storageConfiguration,
  Map<String, String>? tags,
}) async {
  final $payload = <String, dynamic>{
    'knowledgeBaseConfiguration': knowledgeBaseConfiguration,
    'name': name,
    'roleArn': roleArn,
    'clientToken': clientToken ?? _s.generateIdempotencyToken(),
    if (description != null) 'description': description,
    if (storageConfiguration != null)
      'storageConfiguration': storageConfiguration,
    if (tags != null) 'tags': tags,
  };
  final response = await _protocol.send(
    payload: $payload,
    method: 'PUT',
    requestUri: '/knowledgebases/',
    exceptionFnMap: _exceptionFns,
  );
  return CreateKnowledgeBaseResponse.fromJson(response);
}