Syntax Properties Return values Examples

AWS::Bedrock::KnowledgeBase

Specifies a knowledge base as a resource in a top-level template. Minimally, you must specify the following properties:

Name – Specify a name for the knowledge base.
RoleArn – Specify the Amazon Resource Name (ARN) of the IAM role with permissions to invoke API operations on the knowledge base. For more information, see Create a service role for Knowledge base for Amazon Bedrock.
KnowledgeBaseConfiguration – Specify the embeddings configuration of the knowledge base. The following sub-properties are required:
- Type – Specify the value VECTOR.
StorageConfiguration – Specify information about the vector store in which the data source is stored. The following sub-properties are required:
- Type – Specify the vector store service that you are using.
Note
Redis Enterprise Cloud vector stores are currently unsupported in AWS CloudFormation.

For more information about using knowledge bases in Amazon Bedrock, see Knowledge base for Amazon Bedrock.

See the Properties section below for descriptions of both the required and optional properties.

Syntax

To declare this entity in your AWS CloudFormation template, use the following syntax:

JSON


{
  "Type" : "AWS::Bedrock::KnowledgeBase",
  "Properties" : {
      "Description" : String,
      "KnowledgeBaseConfiguration" : KnowledgeBaseConfiguration,
      "Name" : String,
      "RoleArn" : String,
      "StorageConfiguration" : StorageConfiguration,
      "Tags" : {Key: Value, ...}
    }
}

YAML


Type: AWS::Bedrock::KnowledgeBase
Properties:
  Description: String
  KnowledgeBaseConfiguration: 
    KnowledgeBaseConfiguration
  Name: String
  RoleArn: String
  StorageConfiguration: 
    StorageConfiguration
  Tags: 
    Key: Value

Properties

Description

The description of the knowledge base associated with the inline agent.

Required: No

Type: String

Minimum: 1

Maximum: 200

Update requires: No interruption

KnowledgeBaseConfiguration

Contains details about the embeddings configuration of the knowledge base.

Required: Yes

Type: KnowledgeBaseConfiguration

Update requires: Replacement

Name

The name of the knowledge base.

Required: Yes

Type: String

Pattern: ^([0-9a-zA-Z][_-]?){1,100}$

Update requires: No interruption

RoleArn

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

Required: Yes

Type: String

Pattern: ^arn:aws(-[^:]+)?:iam::([0-9]{12})?:role/.+$

Maximum: 2048

Update requires: No interruption

StorageConfiguration

Contains details about the storage configuration of the knowledge base.

Required: Yes

Type: StorageConfiguration

Update requires: Replacement

Tags

Metadata that you can assign to a resource as key-value pairs. For more information, see the following resources:

Required: No

Type: Object of String

Pattern: ^[a-zA-Z0-9\s._:/=+@-]*$

Minimum: 0

Maximum: 256

Update requires: No interruption

Return values

Ref

When you pass the logical ID of this resource to the intrinsic Ref function, Ref returns the knowledge base ID.

For example, { "Ref": "myKnowledgeBase" } could return the value "KB12345678".

For more information about using the Ref function, see Ref.

Fn::GetAtt

The Fn::GetAtt intrinsic function returns a value for a specified attribute of this type. The following are the available attributes and sample return values.

For more information about using the Fn::GetAtt intrinsic function, see Fn::GetAtt.

CreatedAt: The time the knowledge base was created.
FailureReasons: A list of reasons that the API operation on the knowledge base failed.
KnowledgeBaseArn: The Amazon Resource Name (ARN) of the knowledge base.
KnowledgeBaseId: The unique identifier for a knowledge base associated with the inline agent.
Status: The status of the knowledge base.
UpdatedAt: The time the knowledge base was last updated.

Examples

The following examples provide example templates for creating knowledge bases in different vector stores.

Note

Redis Enterprise Cloud vector stores are currently unsupported in AWS CloudFormation.

Create a knowledge base in an Amazon OpenSearch Serverless vector collection.
Create a knowledge base in an Amazon Aurora database cluster.
Create a knowledge base in a Pinecone index.

Create a knowledge base in an Amazon OpenSearch Serverless vector collection.

The following example creates a knowledge base in a vector index within an Amazon OpenSearch Serverless vector collection.

YAML


AWSTemplateFormatVersion: "2010-09-09"
Description: A sample template for Knowledge base with Amazon Opensearch Serverless vector database.
Parameters:
  KnowledgeBaseName:
    Type: String
    Description: The name of the knowledge base.
  KnowledgeBaseDescription:
    Type: String
    Description: The description of the knowledge base.
  DataSourceName:
    Type: String
    Description: The name of the data source.
  DataSourceDescription:
    Type: String
    Description: The description of the data source.
Resources:
  KnowledgeBaseWithAoss:
    Type: AWS::Bedrock::KnowledgeBase
    Properties:
      Name: !Ref KnowledgeBaseName
      Description: !Ref KnowledgeBaseDescription
      RoleArn: "arn:aws:iam::123456789012:role/cfn-local-test-role"
      KnowledgeBaseConfiguration:
        Type: "VECTOR"
        VectorKnowledgeBaseConfiguration:
          EmbeddingModelArn: !Sub "arn:${AWS::Partition}:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1"
      StorageConfiguration:
        Type: "OPENSEARCH_SERVERLESS"
        OpensearchServerlessConfiguration:
          CollectionArn: "arn:aws:aoss:us-west-2:123456789012:collection/abcdefghij1234567890"
          VectorIndexName: "cfn-test-index"
          FieldMapping:
            VectorField: "cfn-test-vector-field"
            TextField: "text"
            MetadataField: "metadata"
  SampleDataSource:
    Type: AWS::Bedrock::DataSource
    Properties:
      KnowledgeBaseId: !Ref KnowledgeBaseWithAoss
      Name: !Ref DataSourceName
      Description: !Ref DataSourceDescription
      DataSourceConfiguration:
        Type: "S3"
        S3Configuration:
          BucketArn: "arn:aws:s3:::kb-test-aws"
          InclusionPrefixes: ["aws-overview.pdf"]

JSON


{
    "AWSTemplateFormatVersion": "2010-09-09",
    "Parameters": {
        "KnowledgeBaseName": {
            "Description": "The name of the knowledge base.",
            "Type": "String"
        },
        "KnowledgeBaseDescription": {
            "Description": "The description of the knowledge base.",
            "Type": "String"
        },
        "DataSourceName": {
            "Description": "The name of the data source.",
            "Type": "String"
        },
        "DataSourceDescription": {
            "Description": "The description of the data source.",
            "Type": "String"
        }
    },
    "Resources": {
        "KnowledgeBaseWithAoss": {
            "Type": "AWS::Bedrock::KnowledgeBase",
            "Properties": {
                "Name": {
                    "Ref": "KnowledgeBaseName"
                },
                "Description": {
                    "Ref": "KnowledgeBaseDescription"
                },
                "RoleArn": "arn:aws:iam::123456789012:role/cfn-local-test-role",
                "KnowledgeBaseConfiguration": {
                    "Type": "VECTOR",
                    "VectorKnowledgeBaseConfiguration": {
                        "EmbeddingModelArn": {
                            "Fn::Sub": "arn:${AWS::Partition}:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1"
                        }
                    }
                },
                "StorageConfiguration": {
                    "Type": "OPENSEARCH_SERVERLESS",
                    "OpensearchServerlessConfiguration": {
                        "CollectionArn": "arn:aws:aoss:us-west-2:123456789012:collection/abcdefghij1234567890",
                        "VectorIndexName": "cfn-test-index",
                        "FieldMapping": {
                            "VectorField": "cfn-test-vector-field",
                            "TextField": "text",
                            "MetadataField": "metadata"
                        }
                    }
                }
            }
        },
        "SampleDataSource": {
            "Type": "AWS::Bedrock::DataSource",
            "Properties": {
                "KnowledgeBaseId": {
                    "Ref": "KnowledgeBaseWithAoss"
                },
                "Name": {
                    "Ref": "DataSourceName"
                },
                "Description": {
                    "Ref": "DataSourceDescription"
                },
                "DataSourceConfiguration": {
                    "Type": "S3",
                    "S3Configuration": {
                        "BucketArn": "arn:aws:s3:::kb-test-aws",
                        "InclusionPrefixes": ["aws-overview.pdf"]
                    }
                }
            }
        }
    }
}

Create a knowledge base in an Amazon Aurora database cluster.

The following example creates a knowledge base in a vector index within an Amazon Aurora database cluster.

YAML


AWSTemplateFormatVersion: "2010-09-09"
Description: A sample template for Knowledge base with RDS vector database.
Parameters:
  KnowledgeBaseName:
    Type: String
    Description: The name of the knowledge base.
  KnolwedgeBaseDescription:
    Type: String
    Description: The description of the knowledge base.
  DataSourceName:
    Type: String
    Description: The name of the data source.
  DataSourceDescription:
    Type: String
    Description: The description of the data source.
Resources:
  KnowledgeBaseWithRDS:
    Type: AWS::Bedrock::KnowledgeBase
    Properties:
      Name: !Ref KnowledgeBaseName
      Description: !Ref KnolwedgeBaseDescription
      RoleArn: "arn:aws:iam::123456789012:role/cfn-local-test-role"
      KnowledgeBaseConfiguration:
        Type: "VECTOR"
        VectorKnowledgeBaseConfiguration:
          EmbeddingModelArn: !Sub "arn:${AWS::Partition}:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1"
      StorageConfiguration:
        Type: "RDS"
        RdsConfiguration:
          ResourceArn: !Sub "arn:${AWS::Partition}:rds:${AWS::Region}:${AWS::AccountId}:cluster:ct-kb-cluster"
          CredentialsSecretArn: !Sub "arn:aws:secretsmanager:${AWS::Region}:${AWS::AccountId}:secret:rds!cluster-4f5961a1-ebd5-4887-818f-0f902e945e04-eFxmC6"
          DatabaseName: "postgres"
          TableName: "bedrock_integration.bedrock_kb"
          FieldMapping:
            VectorField: "embedding"
            TextField: "chunks"
            MetadataField: "metadata"
            PrimaryKeyField: "id"
  SampleDataSource:
    Type: AWS::Bedrock::DataSource
    Properties:
      KnowledgeBaseId: !Ref KnowledgeBaseWithRDS
      Name: !Ref DataSourceName
      Description: !Ref DataSourceDescription
      DataSourceConfiguration:
        Type: "S3"
        S3Configuration:
          BucketArn: "arn:aws:s3:::kb-test-aws"
          InclusionPrefixes: ["aws-overview.pdf"]

JSON


{
    "AWSTemplateFormatVersion": "2010-09-09",
    "Parameters": {
        "KnowledgeBaseName": {
            "Description": "The name of the knowledge base.",
            "Type": "String"
        },
        "KnolwedgeBaseDescription": {
            "Description": "The description of the knowledge base.",
            "Type": "String"
        },
        "DataSourceName": {
            "Description": "The name of the data source.",
            "Type": "String"
        },
        "DataSourceDescription": {
            "Description": "The description of the data source.",
            "Type": "String"
        }
    },
    "Resources": {
        "KnowledgeBaseWithRds": {
            "Type": "AWS::Bedrock::KnowledgeBase",
            "Properties": {
                "Name": {
                    "Ref": "KnowledgeBaseName"
                },
                "Description": {
                    "Ref": "KnolwedgeBaseDescription"
                },
                "RoleArn": "arn:aws:iam::123456789012:role/cfn-local-test-role",
                "KnowledgeBaseConfiguration": {
                    "Type": "VECTOR",
                    "VectorKnowledgeBaseConfiguration": {
                        "EmbeddingModelArn": {
                            "Fn::Sub": "arn:${AWS::Partition}:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1"
                        }
                    }
                },
                "StorageConfiguration": {
                    "Type": "RDS",
                    "RdsConfiguration": {
                        "ResourceArn": {
                            "Fn::Sub": "arn:${AWS::Partition}:rds:${AWS::Region}:${AWS::AccountId}:cluster:knowledgebase-cluster"
                        },
                        "CredentialsSecretArn": {
                            "Fn::Sub": "arn:${AWS::Partition}:secretsmanager:${AWS::Region}:${AWS::AccountId}:secret:rds!cluster-4f5961a1-ebd5-4887-818f-0f902e945e04-eFxmC6"
                        },
                        "DatabaseName": "postgres",
                        "TableName": "bedrock_integration.bedrock_kb",
                        "FieldMapping": {
                            "VectorField": "vectorKey",
                            "TextField": "text",
                            "MetadataField": "metadata",
                            "PrimaryKeyField": "id"
                        }
                    }
                }
            }
        },
        "SampleDataSource": {
            "Type": "AWS::Bedrock::DataSource",
            "Properties": {
                "KnowledgeBaseId": {
                    "Ref": "KnowledgeBaseWithRds"
                },
                "Name": {
                    "Ref": "DataSourceName"
                },
                "Description": {
                    "Ref": "DataSourceDescription"
                },
                "DataSourceConfiguration": {
                    "Type": "S3",
                    "S3Configuration": {
                        "BucketArn": "arn:aws:s3:::kb-test-aws",
                        "InclusionPrefixes": ["aws-overview.pdf"]
                    }
                }
            }
        }
    }
}

Create a knowledge base in a Pinecone index.

The following example creates a knowledge base in a Pinecone index.

YAML


AWSTemplateFormatVersion: "2010-09-09"
Description: A sample template for Knowledge base with Pinecone vector database.
Parameters:
  KnowledgeBaseName:
    Type: String
    Description: The name of the knowledge base.
  KnowledgeBaseDescription:
    Type: String
    Description: The description of the knowledge base.
  DataSourceName:
    Type: String
    Description: The name of the data source.
  DataSourceDescription:
    Type: String
    Description: The description of the data source.
Resources:
  KnowledgeBaseWithPinecone:
    Type: AWS::Bedrock::KnowledgeBase
    Properties:
      Name: !Ref KnowledgeBaseName
      Description: !Ref KnowledgeBaseDescription
      RoleArn: "arn:aws:iam::123456789012:role/cfn-local-test-role"
      KnowledgeBaseConfiguration:
        Type: "VECTOR"
        VectorKnowledgeBaseConfiguration:
          EmbeddingModelArn: !Sub "arn:${AWS::Partition}:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1"
      StorageConfiguration:
        Type: "PINECONE"
        PineconeConfiguration:
          ConnectionString: "https://xxxx.pinecone.io>"
          CredentialsSecretArn: "arn:aws:secretsmanager:us-west-2:123456789012:secret:pinecone-secret-abc123"
          Namespace: "kb-namespace"
          FieldMapping:
            TextField: "text"
            MetadataField: "metadata"
  SampleDataSource:
    Type: AWS::Bedrock::DataSource
    Properties:
      KnowledgeBaseId: !Ref KnowledgeBaseWithPinecone
      Name: !Ref DataSourceName
      Description: !Ref DataSourceDescription
      DataSourceConfiguration:
        Type: "S3"
        S3Configuration:
          BucketArn: "arn:aws:s3:::kb-test-aws"
          InclusionPrefixes: ["aws-overview.pdf"]

JSON


{
    "AWSTemplateFormatVersion": "2010-09-09",
    "Parameters": {
        "KnowledgeBaseName": {
            "Description": "The name of the knowledge base.",
            "Type": "String"
        },
        "KnowledgeBaseDescription": {
            "Description": "The description of the knowledge base.",
            "Type": "String"
        },
        "DataSourceName": {
            "Description": "The name of the data source.",
            "Type": "String"
        },
        "DataSourceDescription": {
            "Description": "The description of the data source.",
            "Type": "String"
        }
    },
    "Resources": {
        "KnowledgeBaseWithPinecone": {
            "Type": "AWS::Bedrock::KnowledgeBase",
            "Properties": {
                "Name": {
                    "Ref": "KnowledgeBaseName"
                },
                "Description": {
                    "Ref": "KnowledgeBaseDescription"
                },
                "RoleArn": "arn:aws:iam::123456789012:role/cfn-local-test-role",
                "KnowledgeBaseConfiguration": {
                    "Type": "VECTOR",
                    "VectorKnowledgeBaseConfiguration": {
                        "EmbeddingModelArn": {
                            "Fn::Sub": "arn:${AWS::Partition}:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1"
                        }
                    }
                },
                "StorageConfiguration": {
                    "Type": "PINECONE",
                    "PineconeConfiguration": {
                        "ConnectionString": "https://xxxx.pinecone.io",
                        "CredentialsSecretArn": "arn:aws:secretsmanager:us-west-2:123456789012:secret:pinecone-secret-abc123",
                        "Namespace": "kb-namespace",
                        "FieldMapping": {
                            "TextField": "text",
                            "MetadataField": "metadata"
                        }
                    }
                }
            }
        },
        "SampleDataSource": {
            "Type": "AWS::Bedrock::DataSource",
            "Properties": {
                "KnowledgeBaseId": {
                    "Ref": "KnowledgeBaseWithPinecone"
                },
                "Name": {
                    "Ref": "DataSourceName"
                },
                "Description": {
                    "Ref": "DataSourceDescription"
                },
                "DataSourceConfiguration": {
                    "Type": "S3",
                    "S3Configuration": {
                        "BucketArn": "arn:aws:s3:::kb-test-aws",
                        "InclusionPrefixes": ["aws-overview.pdf"]
                    }
                }
            }
        }
    }
}

Warning Javascript is disabled or is unavailable in your browser.

To use the Amazon Web Services Documentation, Javascript must be enabled. Please refer to your browser's Help pages for instructions.

Document Conventions

AWS::Bedrock::GuardrailVersion

BedrockEmbeddingModelConfiguration