CfnKnowledgeBasePropsMixin

class aws_cdk.mixins_preview.aws_bedrock.mixins.CfnKnowledgeBasePropsMixin(props, *, strategy=None)

Bases: Mixin

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.

Redis Enterprise Cloud vector stores are currently unsupported in 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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-bedrock-knowledgebase.html

CloudformationResource:

AWS::Bedrock::KnowledgeBase

Mixin:

true

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview import mixins
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

cfn_knowledge_base_props_mixin = bedrock_mixins.CfnKnowledgeBasePropsMixin(bedrock_mixins.CfnKnowledgeBaseMixinProps(
    description="description",
    knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.KnowledgeBaseConfigurationProperty(
        kendra_knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.KendraKnowledgeBaseConfigurationProperty(
            kendra_index_arn="kendraIndexArn"
        ),
        sql_knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.SqlKnowledgeBaseConfigurationProperty(
            redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftConfigurationProperty(
                query_engine_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineConfigurationProperty(
                    provisioned_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(
                        auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
                            database_user="databaseUser",
                            type="type",
                            username_password_secret_arn="usernamePasswordSecretArn"
                        ),
                        cluster_identifier="clusterIdentifier"
                    ),
                    serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(
                        auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
                            type="type",
                            username_password_secret_arn="usernamePasswordSecretArn"
                        ),
                        workgroup_arn="workgroupArn"
                    ),
                    type="type"
                ),
                query_generation_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationConfigurationProperty(
                    execution_timeout_seconds=123,
                    generation_context=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationContextProperty(
                        curated_queries=[bedrock_mixins.CfnKnowledgeBasePropsMixin.CuratedQueryProperty(
                            natural_language="naturalLanguage",
                            sql="sql"
                        )],
                        tables=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(
                            columns=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
                                description="description",
                                inclusion="inclusion",
                                name="name"
                            )],
                            description="description",
                            inclusion="inclusion",
                            name="name"
                        )]
                    )
                ),
                storage_configurations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineStorageConfigurationProperty(
                    aws_data_catalog_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(
                        table_names=["tableNames"]
                    ),
                    redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(
                        database_name="databaseName"
                    ),
                    type="type"
                )]
            ),
            type="type"
        ),
        type="type",
        vector_knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.VectorKnowledgeBaseConfigurationProperty(
            embedding_model_arn="embeddingModelArn",
            embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.EmbeddingModelConfigurationProperty(
                bedrock_embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.BedrockEmbeddingModelConfigurationProperty(
                    dimensions=123,
                    embedding_data_type="embeddingDataType"
                )
            ),
            supplemental_data_storage_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageConfigurationProperty(
                supplemental_data_storage_locations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageLocationProperty(
                    s3_location=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3LocationProperty(
                        uri="uri"
                    ),
                    supplemental_data_storage_location_type="supplementalDataStorageLocationType"
                )]
            )
        )
    ),
    name="name",
    role_arn="roleArn",
    storage_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.StorageConfigurationProperty(
        mongo_db_atlas_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasConfigurationProperty(
            collection_name="collectionName",
            credentials_secret_arn="credentialsSecretArn",
            database_name="databaseName",
            endpoint="endpoint",
            endpoint_service_name="endpointServiceName",
            field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasFieldMappingProperty(
                metadata_field="metadataField",
                text_field="textField",
                vector_field="vectorField"
            ),
            text_index_name="textIndexName",
            vector_index_name="vectorIndexName"
        ),
        neptune_analytics_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsConfigurationProperty(
            field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsFieldMappingProperty(
                metadata_field="metadataField",
                text_field="textField"
            ),
            graph_arn="graphArn"
        ),
        opensearch_managed_cluster_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterConfigurationProperty(
            domain_arn="domainArn",
            domain_endpoint="domainEndpoint",
            field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterFieldMappingProperty(
                metadata_field="metadataField",
                text_field="textField",
                vector_field="vectorField"
            ),
            vector_index_name="vectorIndexName"
        ),
        opensearch_serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessConfigurationProperty(
            collection_arn="collectionArn",
            field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessFieldMappingProperty(
                metadata_field="metadataField",
                text_field="textField",
                vector_field="vectorField"
            ),
            vector_index_name="vectorIndexName"
        ),
        pinecone_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeConfigurationProperty(
            connection_string="connectionString",
            credentials_secret_arn="credentialsSecretArn",
            field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeFieldMappingProperty(
                metadata_field="metadataField",
                text_field="textField"
            ),
            namespace="namespace"
        ),
        rds_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsConfigurationProperty(
            credentials_secret_arn="credentialsSecretArn",
            database_name="databaseName",
            field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsFieldMappingProperty(
                custom_metadata_field="customMetadataField",
                metadata_field="metadataField",
                primary_key_field="primaryKeyField",
                text_field="textField",
                vector_field="vectorField"
            ),
            resource_arn="resourceArn",
            table_name="tableName"
        ),
        s3_vectors_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3VectorsConfigurationProperty(
            index_arn="indexArn",
            index_name="indexName",
            vector_bucket_arn="vectorBucketArn"
        ),
        type="type"
    ),
    tags={
        "tags_key": "tags"
    }
),
    strategy=mixins.PropertyMergeStrategy.OVERRIDE
)

Create a mixin to apply properties to AWS::Bedrock::KnowledgeBase.

Parameters:

• props (Union[CfnKnowledgeBaseMixinProps, Dict[str, Any]]) – L1 properties to apply.

• strategy (Optional[PropertyMergeStrategy]) – (experimental) Strategy for merging nested properties. Default: - PropertyMergeStrategy.MERGE

Methods

apply_to(construct)

Apply the mixin properties to the construct.

Parameters:

construct (IConstruct)

Return type:

IConstruct

supports(construct)

Check if this mixin supports the given construct.

Parameters:

construct (IConstruct)

Return type:

bool

Attributes

CFN_PROPERTY_KEYS = ['description', 'knowledgeBaseConfiguration', 'name', 'roleArn', 'storageConfiguration', 'tags']

Static Methods

classmethod is_mixin(x)

(experimental) Checks if x is a Mixin.

Parameters:

x (Any) – Any object.

Return type:

bool

Returns:

true if x is an object created from a class which extends Mixin.

Stability:

experimental

BedrockEmbeddingModelConfigurationProperty

class CfnKnowledgeBasePropsMixin.BedrockEmbeddingModelConfigurationProperty(*, dimensions=None, embedding_data_type=None)

Bases: object

The vector configuration details for the Bedrock embeddings model.

Parameters:

• dimensions (Union[int, float, None]) – The dimensions details for the vector configuration used on the Bedrock embeddings model.

• embedding_data_type (Optional[str]) – The data type for the vectors when using a model to convert text into vector embeddings. The model must support the specified data type for vector embeddings. Floating-point (float32) is the default data type, and is supported by most models for vector embeddings. See Supported embeddings models for information on the available models and their vector data types.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-bedrockembeddingmodelconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

bedrock_embedding_model_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.BedrockEmbeddingModelConfigurationProperty(
    dimensions=123,
    embedding_data_type="embeddingDataType"
)

Attributes

dimensions

The dimensions details for the vector configuration used on the Bedrock embeddings model.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-bedrockembeddingmodelconfiguration.html#cfn-bedrock-knowledgebase-bedrockembeddingmodelconfiguration-dimensions

embedding_data_type

The data type for the vectors when using a model to convert text into vector embeddings.

The model must support the specified data type for vector embeddings. Floating-point (float32) is the default data type, and is supported by most models for vector embeddings. See Supported embeddings models for information on the available models and their vector data types.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-bedrockembeddingmodelconfiguration.html#cfn-bedrock-knowledgebase-bedrockembeddingmodelconfiguration-embeddingdatatype

CuratedQueryProperty

class CfnKnowledgeBasePropsMixin.CuratedQueryProperty(*, natural_language=None, sql=None)

Bases: object

Contains configurations for a query, each of which defines information about example queries to help the query engine generate appropriate SQL queries.

Parameters:

• natural_language (Optional[str]) – An example natural language query.

• sql (Optional[str]) – The SQL equivalent of the natural language query.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-curatedquery.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

curated_query_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.CuratedQueryProperty(
    natural_language="naturalLanguage",
    sql="sql"
)

Attributes

natural_language

An example natural language query.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-curatedquery.html#cfn-bedrock-knowledgebase-curatedquery-naturallanguage

sql

The SQL equivalent of the natural language query.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-curatedquery.html#cfn-bedrock-knowledgebase-curatedquery-sql

EmbeddingModelConfigurationProperty

class CfnKnowledgeBasePropsMixin.EmbeddingModelConfigurationProperty(*, bedrock_embedding_model_configuration=None)

Bases: object

The configuration details for the embeddings model.

Parameters:

bedrock_embedding_model_configuration (Union[IResolvable, BedrockEmbeddingModelConfigurationProperty, Dict[str, Any], None]) – The vector configuration details on the Bedrock embeddings model.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-embeddingmodelconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

embedding_model_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.EmbeddingModelConfigurationProperty(
    bedrock_embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.BedrockEmbeddingModelConfigurationProperty(
        dimensions=123,
        embedding_data_type="embeddingDataType"
    )
)

Attributes

bedrock_embedding_model_configuration

The vector configuration details on the Bedrock embeddings model.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-embeddingmodelconfiguration.html#cfn-bedrock-knowledgebase-embeddingmodelconfiguration-bedrockembeddingmodelconfiguration

KendraKnowledgeBaseConfigurationProperty

class CfnKnowledgeBasePropsMixin.KendraKnowledgeBaseConfigurationProperty(*, kendra_index_arn=None)

Bases: object

Settings for an Amazon Kendra knowledge base.

Parameters:

kendra_index_arn (Optional[str]) – The ARN of the Amazon Kendra index.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-kendraknowledgebaseconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

kendra_knowledge_base_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.KendraKnowledgeBaseConfigurationProperty(
    kendra_index_arn="kendraIndexArn"
)

Attributes

kendra_index_arn

The ARN of the Amazon Kendra index.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-kendraknowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-kendraknowledgebaseconfiguration-kendraindexarn

KnowledgeBaseConfigurationProperty

class CfnKnowledgeBasePropsMixin.KnowledgeBaseConfigurationProperty(*, kendra_knowledge_base_configuration=None, sql_knowledge_base_configuration=None, type=None, vector_knowledge_base_configuration=None)

Bases: object

Configurations to apply to a knowledge base attached to the agent during query.

For more information, see Knowledge base retrieval configurations .

Parameters:

• kendra_knowledge_base_configuration (Union[IResolvable, KendraKnowledgeBaseConfigurationProperty, Dict[str, Any], None]) – Settings for an Amazon Kendra knowledge base.

• sql_knowledge_base_configuration (Union[IResolvable, SqlKnowledgeBaseConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for a knowledge base connected to an SQL database.

• type (Optional[str]) – The type of data that the data source is converted into for the knowledge base.

• vector_knowledge_base_configuration (Union[IResolvable, VectorKnowledgeBaseConfigurationProperty, Dict[str, Any], None]) – Contains details about the model that’s used to convert the data source into vector embeddings.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-knowledgebaseconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

knowledge_base_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.KnowledgeBaseConfigurationProperty(
    kendra_knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.KendraKnowledgeBaseConfigurationProperty(
        kendra_index_arn="kendraIndexArn"
    ),
    sql_knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.SqlKnowledgeBaseConfigurationProperty(
        redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftConfigurationProperty(
            query_engine_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineConfigurationProperty(
                provisioned_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(
                    auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
                        database_user="databaseUser",
                        type="type",
                        username_password_secret_arn="usernamePasswordSecretArn"
                    ),
                    cluster_identifier="clusterIdentifier"
                ),
                serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(
                    auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
                        type="type",
                        username_password_secret_arn="usernamePasswordSecretArn"
                    ),
                    workgroup_arn="workgroupArn"
                ),
                type="type"
            ),
            query_generation_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationConfigurationProperty(
                execution_timeout_seconds=123,
                generation_context=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationContextProperty(
                    curated_queries=[bedrock_mixins.CfnKnowledgeBasePropsMixin.CuratedQueryProperty(
                        natural_language="naturalLanguage",
                        sql="sql"
                    )],
                    tables=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(
                        columns=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
                            description="description",
                            inclusion="inclusion",
                            name="name"
                        )],
                        description="description",
                        inclusion="inclusion",
                        name="name"
                    )]
                )
            ),
            storage_configurations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineStorageConfigurationProperty(
                aws_data_catalog_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(
                    table_names=["tableNames"]
                ),
                redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(
                    database_name="databaseName"
                ),
                type="type"
            )]
        ),
        type="type"
    ),
    type="type",
    vector_knowledge_base_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.VectorKnowledgeBaseConfigurationProperty(
        embedding_model_arn="embeddingModelArn",
        embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.EmbeddingModelConfigurationProperty(
            bedrock_embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.BedrockEmbeddingModelConfigurationProperty(
                dimensions=123,
                embedding_data_type="embeddingDataType"
            )
        ),
        supplemental_data_storage_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageConfigurationProperty(
            supplemental_data_storage_locations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageLocationProperty(
                s3_location=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3LocationProperty(
                    uri="uri"
                ),
                supplemental_data_storage_location_type="supplementalDataStorageLocationType"
            )]
        )
    )
)

Attributes

kendra_knowledge_base_configuration

Settings for an Amazon Kendra knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-knowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-knowledgebaseconfiguration-kendraknowledgebaseconfiguration

sql_knowledge_base_configuration

Specifies configurations for a knowledge base connected to an SQL database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-knowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-knowledgebaseconfiguration-sqlknowledgebaseconfiguration

type

The type of data that the data source is converted into for the knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-knowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-knowledgebaseconfiguration-type

vector_knowledge_base_configuration

Contains details about the model that’s used to convert the data source into vector embeddings.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-knowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-knowledgebaseconfiguration-vectorknowledgebaseconfiguration

MongoDbAtlasConfigurationProperty

class CfnKnowledgeBasePropsMixin.MongoDbAtlasConfigurationProperty(*, collection_name=None, credentials_secret_arn=None, database_name=None, endpoint=None, endpoint_service_name=None, field_mapping=None, text_index_name=None, vector_index_name=None)

Bases: object

Contains details about the storage configuration of the knowledge base in MongoDB Atlas.

Parameters:

• collection_name (Optional[str]) – The collection name of the knowledge base in MongoDB Atlas.

• credentials_secret_arn (Optional[str]) – The Amazon Resource Name (ARN) of the secret that you created in AWS Secrets Manager that contains user credentials for your MongoDB Atlas cluster.

• database_name (Optional[str]) – The database name in your MongoDB Atlas cluster for your knowledge base.

• endpoint (Optional[str]) – The endpoint URL of your MongoDB Atlas cluster for your knowledge base.

• endpoint_service_name (Optional[str]) – The name of the VPC endpoint service in your account that is connected to your MongoDB Atlas cluster.

• field_mapping (Union[IResolvable, MongoDbAtlasFieldMappingProperty, Dict[str, Any], None]) – Contains the names of the fields to which to map information about the vector store.

• text_index_name (Optional[str]) – The name of the text search index in the MongoDB collection. This is required for using the hybrid search feature.

• vector_index_name (Optional[str]) – The name of the MongoDB Atlas vector search index.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

mongo_db_atlas_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasConfigurationProperty(
    collection_name="collectionName",
    credentials_secret_arn="credentialsSecretArn",
    database_name="databaseName",
    endpoint="endpoint",
    endpoint_service_name="endpointServiceName",
    field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasFieldMappingProperty(
        metadata_field="metadataField",
        text_field="textField",
        vector_field="vectorField"
    ),
    text_index_name="textIndexName",
    vector_index_name="vectorIndexName"
)

Attributes

collection_name

The collection name of the knowledge base in MongoDB Atlas.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-collectionname

credentials_secret_arn

The Amazon Resource Name (ARN) of the secret that you created in AWS Secrets Manager that contains user credentials for your MongoDB Atlas cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-credentialssecretarn

database_name

The database name in your MongoDB Atlas cluster for your knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-databasename

endpoint

The endpoint URL of your MongoDB Atlas cluster for your knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-endpoint

endpoint_service_name

The name of the VPC endpoint service in your account that is connected to your MongoDB Atlas cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-endpointservicename

field_mapping

Contains the names of the fields to which to map information about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-fieldmapping

text_index_name

The name of the text search index in the MongoDB collection.

This is required for using the hybrid search feature.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-textindexname

vector_index_name

The name of the MongoDB Atlas vector search index.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasconfiguration.html#cfn-bedrock-knowledgebase-mongodbatlasconfiguration-vectorindexname

MongoDbAtlasFieldMappingProperty

class CfnKnowledgeBasePropsMixin.MongoDbAtlasFieldMappingProperty(*, metadata_field=None, text_field=None, vector_field=None)

Bases: object

Contains the names of the fields to which to map information about the vector store.

Parameters:

• metadata_field (Optional[str]) – The name of the field in which Amazon Bedrock stores metadata about the vector store.

• text_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.

• vector_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasfieldmapping.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

mongo_db_atlas_field_mapping_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasFieldMappingProperty(
    metadata_field="metadataField",
    text_field="textField",
    vector_field="vectorField"
)

Attributes

metadata_field

The name of the field in which Amazon Bedrock stores metadata about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasfieldmapping.html#cfn-bedrock-knowledgebase-mongodbatlasfieldmapping-metadatafield

text_field

The name of the field in which Amazon Bedrock stores the raw text from your data.

The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasfieldmapping.html#cfn-bedrock-knowledgebase-mongodbatlasfieldmapping-textfield

vector_field

The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-mongodbatlasfieldmapping.html#cfn-bedrock-knowledgebase-mongodbatlasfieldmapping-vectorfield

NeptuneAnalyticsConfigurationProperty

class CfnKnowledgeBasePropsMixin.NeptuneAnalyticsConfigurationProperty(*, field_mapping=None, graph_arn=None)

Bases: object

Contains details about the storage configuration of the knowledge base in Amazon Neptune Analytics.

For more information, see Create a vector index in Amazon Neptune Analytics .

Parameters:

• field_mapping (Union[IResolvable, NeptuneAnalyticsFieldMappingProperty, Dict[str, Any], None]) – Contains the names of the fields to which to map information about the vector store.

• graph_arn (Optional[str]) – The Amazon Resource Name (ARN) of the Neptune Analytics vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-neptuneanalyticsconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

neptune_analytics_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsConfigurationProperty(
    field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsFieldMappingProperty(
        metadata_field="metadataField",
        text_field="textField"
    ),
    graph_arn="graphArn"
)

Attributes

field_mapping

Contains the names of the fields to which to map information about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-neptuneanalyticsconfiguration.html#cfn-bedrock-knowledgebase-neptuneanalyticsconfiguration-fieldmapping

graph_arn

The Amazon Resource Name (ARN) of the Neptune Analytics vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-neptuneanalyticsconfiguration.html#cfn-bedrock-knowledgebase-neptuneanalyticsconfiguration-grapharn

NeptuneAnalyticsFieldMappingProperty

class CfnKnowledgeBasePropsMixin.NeptuneAnalyticsFieldMappingProperty(*, metadata_field=None, text_field=None)

Bases: object

Contains the names of the fields to which to map information about the vector store.

Parameters:

• metadata_field (Optional[str]) – The name of the field in which Amazon Bedrock stores metadata about the vector store.

• text_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-neptuneanalyticsfieldmapping.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

neptune_analytics_field_mapping_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsFieldMappingProperty(
    metadata_field="metadataField",
    text_field="textField"
)

Attributes

metadata_field

The name of the field in which Amazon Bedrock stores metadata about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-neptuneanalyticsfieldmapping.html#cfn-bedrock-knowledgebase-neptuneanalyticsfieldmapping-metadatafield

text_field

The name of the field in which Amazon Bedrock stores the raw text from your data.

The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-neptuneanalyticsfieldmapping.html#cfn-bedrock-knowledgebase-neptuneanalyticsfieldmapping-textfield

OpenSearchManagedClusterConfigurationProperty

class CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterConfigurationProperty(*, domain_arn=None, domain_endpoint=None, field_mapping=None, vector_index_name=None)

Bases: object

Contains details about the Managed Cluster configuration of the knowledge base in Amazon OpenSearch Service.

For more information, see Create a vector index in OpenSearch Managed Cluster .

Parameters:

• domain_arn (Optional[str]) – The Amazon Resource Name (ARN) of the OpenSearch domain.

• domain_endpoint (Optional[str]) – The endpoint URL the OpenSearch domain.

• field_mapping (Union[IResolvable, OpenSearchManagedClusterFieldMappingProperty, Dict[str, Any], None]) – Contains the names of the fields to which to map information about the vector store.

• vector_index_name (Optional[str]) – The name of the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

open_search_managed_cluster_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterConfigurationProperty(
    domain_arn="domainArn",
    domain_endpoint="domainEndpoint",
    field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterFieldMappingProperty(
        metadata_field="metadataField",
        text_field="textField",
        vector_field="vectorField"
    ),
    vector_index_name="vectorIndexName"
)

Attributes

domain_arn

The Amazon Resource Name (ARN) of the OpenSearch domain.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterconfiguration.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterconfiguration-domainarn

domain_endpoint

The endpoint URL the OpenSearch domain.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterconfiguration.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterconfiguration-domainendpoint

field_mapping

Contains the names of the fields to which to map information about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterconfiguration.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterconfiguration-fieldmapping

vector_index_name

The name of the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterconfiguration.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterconfiguration-vectorindexname

OpenSearchManagedClusterFieldMappingProperty

class CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterFieldMappingProperty(*, metadata_field=None, text_field=None, vector_field=None)

Bases: object

Contains the names of the fields to which to map information about the vector store.

Parameters:

• metadata_field (Optional[str]) – The name of the field in which Amazon Bedrock stores metadata about the vector store.

• text_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.

• vector_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

open_search_managed_cluster_field_mapping_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterFieldMappingProperty(
    metadata_field="metadataField",
    text_field="textField",
    vector_field="vectorField"
)

Attributes

metadata_field

The name of the field in which Amazon Bedrock stores metadata about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping-metadatafield

text_field

The name of the field in which Amazon Bedrock stores the raw text from your data.

The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping-textfield

vector_field

The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping.html#cfn-bedrock-knowledgebase-opensearchmanagedclusterfieldmapping-vectorfield

OpenSearchServerlessConfigurationProperty

class CfnKnowledgeBasePropsMixin.OpenSearchServerlessConfigurationProperty(*, collection_arn=None, field_mapping=None, vector_index_name=None)

Bases: object

Contains details about the storage configuration of the knowledge base in Amazon OpenSearch Service.

For more information, see Create a vector index in Amazon OpenSearch Service .

Parameters:

• collection_arn (Optional[str]) – The Amazon Resource Name (ARN) of the OpenSearch Service vector store.

• field_mapping (Union[IResolvable, OpenSearchServerlessFieldMappingProperty, Dict[str, Any], None]) – Contains the names of the fields to which to map information about the vector store.

• vector_index_name (Optional[str]) – The name of the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

open_search_serverless_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessConfigurationProperty(
    collection_arn="collectionArn",
    field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessFieldMappingProperty(
        metadata_field="metadataField",
        text_field="textField",
        vector_field="vectorField"
    ),
    vector_index_name="vectorIndexName"
)

Attributes

collection_arn

The Amazon Resource Name (ARN) of the OpenSearch Service vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessconfiguration.html#cfn-bedrock-knowledgebase-opensearchserverlessconfiguration-collectionarn

field_mapping

Contains the names of the fields to which to map information about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessconfiguration.html#cfn-bedrock-knowledgebase-opensearchserverlessconfiguration-fieldmapping

vector_index_name

The name of the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessconfiguration.html#cfn-bedrock-knowledgebase-opensearchserverlessconfiguration-vectorindexname

OpenSearchServerlessFieldMappingProperty

class CfnKnowledgeBasePropsMixin.OpenSearchServerlessFieldMappingProperty(*, metadata_field=None, text_field=None, vector_field=None)

Bases: object

Contains the names of the fields to which to map information about the vector store.

Parameters:

• metadata_field (Optional[str]) – The name of the field in which Amazon Bedrock stores metadata about the vector store.

• text_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.

• vector_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessfieldmapping.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

open_search_serverless_field_mapping_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessFieldMappingProperty(
    metadata_field="metadataField",
    text_field="textField",
    vector_field="vectorField"
)

Attributes

metadata_field

The name of the field in which Amazon Bedrock stores metadata about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessfieldmapping.html#cfn-bedrock-knowledgebase-opensearchserverlessfieldmapping-metadatafield

text_field

The name of the field in which Amazon Bedrock stores the raw text from your data.

The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessfieldmapping.html#cfn-bedrock-knowledgebase-opensearchserverlessfieldmapping-textfield

vector_field

The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-opensearchserverlessfieldmapping.html#cfn-bedrock-knowledgebase-opensearchserverlessfieldmapping-vectorfield

PineconeConfigurationProperty

class CfnKnowledgeBasePropsMixin.PineconeConfigurationProperty(*, connection_string=None, credentials_secret_arn=None, field_mapping=None, namespace=None)

Bases: object

Contains details about the storage configuration of the knowledge base in Pinecone.

For more information, see Create a vector index in Pinecone .

Parameters:

• connection_string (Optional[str]) – The endpoint URL for your index management page.

• credentials_secret_arn (Optional[str]) – The Amazon Resource Name (ARN) of the secret that you created in AWS Secrets Manager that is linked to your Pinecone API key.

• field_mapping (Union[IResolvable, PineconeFieldMappingProperty, Dict[str, Any], None]) – Contains the names of the fields to which to map information about the vector store.

• namespace (Optional[str]) – The namespace to be used to write new data to your database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconeconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

pinecone_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeConfigurationProperty(
    connection_string="connectionString",
    credentials_secret_arn="credentialsSecretArn",
    field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeFieldMappingProperty(
        metadata_field="metadataField",
        text_field="textField"
    ),
    namespace="namespace"
)

Attributes

connection_string

The endpoint URL for your index management page.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconeconfiguration.html#cfn-bedrock-knowledgebase-pineconeconfiguration-connectionstring

credentials_secret_arn

The Amazon Resource Name (ARN) of the secret that you created in AWS Secrets Manager that is linked to your Pinecone API key.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconeconfiguration.html#cfn-bedrock-knowledgebase-pineconeconfiguration-credentialssecretarn

field_mapping

Contains the names of the fields to which to map information about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconeconfiguration.html#cfn-bedrock-knowledgebase-pineconeconfiguration-fieldmapping

namespace

The namespace to be used to write new data to your database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconeconfiguration.html#cfn-bedrock-knowledgebase-pineconeconfiguration-namespace

PineconeFieldMappingProperty

class CfnKnowledgeBasePropsMixin.PineconeFieldMappingProperty(*, metadata_field=None, text_field=None)

Bases: object

Contains the names of the fields to which to map information about the vector store.

Parameters:

• metadata_field (Optional[str]) – The name of the field in which Amazon Bedrock stores metadata about the vector store.

• text_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconefieldmapping.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

pinecone_field_mapping_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeFieldMappingProperty(
    metadata_field="metadataField",
    text_field="textField"
)

Attributes

metadata_field

The name of the field in which Amazon Bedrock stores metadata about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconefieldmapping.html#cfn-bedrock-knowledgebase-pineconefieldmapping-metadatafield

text_field

The name of the field in which Amazon Bedrock stores the raw text from your data.

The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-pineconefieldmapping.html#cfn-bedrock-knowledgebase-pineconefieldmapping-textfield

QueryGenerationColumnProperty

class CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(*, description=None, inclusion=None, name=None)

Bases: object

Contains information about a column in the current table for the query engine to consider.

Parameters:

• description (Optional[str]) – A description of the column that helps the query engine understand the contents of the column.

• inclusion (Optional[str]) – Specifies whether to include or exclude the column during query generation. If you specify EXCLUDE , the column will be ignored. If you specify INCLUDE , all other columns in the table will be ignored.

• name (Optional[str]) – The name of the column for which the other fields in this object apply.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationcolumn.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

query_generation_column_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
    description="description",
    inclusion="inclusion",
    name="name"
)

Attributes

description

A description of the column that helps the query engine understand the contents of the column.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationcolumn.html#cfn-bedrock-knowledgebase-querygenerationcolumn-description

inclusion

Specifies whether to include or exclude the column during query generation.

If you specify EXCLUDE , the column will be ignored. If you specify INCLUDE , all other columns in the table will be ignored.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationcolumn.html#cfn-bedrock-knowledgebase-querygenerationcolumn-inclusion

name

The name of the column for which the other fields in this object apply.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationcolumn.html#cfn-bedrock-knowledgebase-querygenerationcolumn-name

QueryGenerationConfigurationProperty

class CfnKnowledgeBasePropsMixin.QueryGenerationConfigurationProperty(*, execution_timeout_seconds=None, generation_context=None)

Bases: object

Contains configurations for query generation.

For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide..

Parameters:

• execution_timeout_seconds (Union[int, float, None]) – The time after which query generation will time out.

• generation_context (Union[IResolvable, QueryGenerationContextProperty, Dict[str, Any], None]) – Specifies configurations for context to use during query generation.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

query_generation_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationConfigurationProperty(
    execution_timeout_seconds=123,
    generation_context=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationContextProperty(
        curated_queries=[bedrock_mixins.CfnKnowledgeBasePropsMixin.CuratedQueryProperty(
            natural_language="naturalLanguage",
            sql="sql"
        )],
        tables=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(
            columns=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
                description="description",
                inclusion="inclusion",
                name="name"
            )],
            description="description",
            inclusion="inclusion",
            name="name"
        )]
    )
)

Attributes

execution_timeout_seconds

The time after which query generation will time out.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationconfiguration.html#cfn-bedrock-knowledgebase-querygenerationconfiguration-executiontimeoutseconds

generation_context

Specifies configurations for context to use during query generation.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationconfiguration.html#cfn-bedrock-knowledgebase-querygenerationconfiguration-generationcontext

QueryGenerationContextProperty

class CfnKnowledgeBasePropsMixin.QueryGenerationContextProperty(*, curated_queries=None, tables=None)

Bases: object

Contains configurations for context to use during query generation.

Attributes

curated_queries

An array of objects, each of which defines information about example queries to help the query engine generate appropriate SQL queries.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationcontext.html#cfn-bedrock-knowledgebase-querygenerationcontext-curatedqueries

tables

An array of objects, each of which defines information about a table in the database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationcontext.html#cfn-bedrock-knowledgebase-querygenerationcontext-tables

QueryGenerationTableProperty

class CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(*, columns=None, description=None, inclusion=None, name=None)

Bases: object

Contains information about a table for the query engine to consider.

Parameters:

• columns (Union[IResolvable, Sequence[Union[IResolvable, QueryGenerationColumnProperty, Dict[str, Any]]], None]) – An array of objects, each of which defines information about a column in the table.

• description (Optional[str]) – A description of the table that helps the query engine understand the contents of the table.

• inclusion (Optional[str]) – Specifies whether to include or exclude the table during query generation. If you specify EXCLUDE , the table will be ignored. If you specify INCLUDE , all other tables will be ignored.

• name (Optional[str]) – The name of the table for which the other fields in this object apply.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationtable.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

query_generation_table_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(
    columns=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
        description="description",
        inclusion="inclusion",
        name="name"
    )],
    description="description",
    inclusion="inclusion",
    name="name"
)

Attributes

columns

An array of objects, each of which defines information about a column in the table.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationtable.html#cfn-bedrock-knowledgebase-querygenerationtable-columns

description

A description of the table that helps the query engine understand the contents of the table.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationtable.html#cfn-bedrock-knowledgebase-querygenerationtable-description

inclusion

Specifies whether to include or exclude the table during query generation.

If you specify EXCLUDE , the table will be ignored. If you specify INCLUDE , all other tables will be ignored.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationtable.html#cfn-bedrock-knowledgebase-querygenerationtable-inclusion

name

The name of the table for which the other fields in this object apply.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-querygenerationtable.html#cfn-bedrock-knowledgebase-querygenerationtable-name

RdsConfigurationProperty

class CfnKnowledgeBasePropsMixin.RdsConfigurationProperty(*, credentials_secret_arn=None, database_name=None, field_mapping=None, resource_arn=None, table_name=None)

Bases: object

Contains details about the storage configuration of the knowledge base in Amazon RDS.

For more information, see Create a vector index in Amazon RDS .

Parameters:

• credentials_secret_arn (Optional[str]) – The Amazon Resource Name (ARN) of the secret that you created in AWS Secrets Manager that is linked to your Amazon RDS database.

• database_name (Optional[str]) – The name of your Amazon RDS database.

• field_mapping (Union[IResolvable, RdsFieldMappingProperty, Dict[str, Any], None]) – Contains the names of the fields to which to map information about the vector store.

• resource_arn (Optional[str]) – The Amazon Resource Name (ARN) of the vector store.

• table_name (Optional[str]) – The name of the table in the database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

rds_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsConfigurationProperty(
    credentials_secret_arn="credentialsSecretArn",
    database_name="databaseName",
    field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsFieldMappingProperty(
        custom_metadata_field="customMetadataField",
        metadata_field="metadataField",
        primary_key_field="primaryKeyField",
        text_field="textField",
        vector_field="vectorField"
    ),
    resource_arn="resourceArn",
    table_name="tableName"
)

Attributes

credentials_secret_arn

The Amazon Resource Name (ARN) of the secret that you created in AWS Secrets Manager that is linked to your Amazon RDS database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsconfiguration.html#cfn-bedrock-knowledgebase-rdsconfiguration-credentialssecretarn

database_name

The name of your Amazon RDS database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsconfiguration.html#cfn-bedrock-knowledgebase-rdsconfiguration-databasename

field_mapping

Contains the names of the fields to which to map information about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsconfiguration.html#cfn-bedrock-knowledgebase-rdsconfiguration-fieldmapping

resource_arn

The Amazon Resource Name (ARN) of the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsconfiguration.html#cfn-bedrock-knowledgebase-rdsconfiguration-resourcearn

table_name

The name of the table in the database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsconfiguration.html#cfn-bedrock-knowledgebase-rdsconfiguration-tablename

RdsFieldMappingProperty

class CfnKnowledgeBasePropsMixin.RdsFieldMappingProperty(*, custom_metadata_field=None, metadata_field=None, primary_key_field=None, text_field=None, vector_field=None)

Bases: object

Contains the names of the fields to which to map information about the vector store.

Parameters:

• custom_metadata_field (Optional[str]) – Provide a name for the universal metadata field where Amazon Bedrock will store any custom metadata from your data source.

• metadata_field (Optional[str]) – The name of the field in which Amazon Bedrock stores metadata about the vector store.

• primary_key_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the ID for each entry.

• text_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.

• vector_field (Optional[str]) – The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsfieldmapping.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

rds_field_mapping_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsFieldMappingProperty(
    custom_metadata_field="customMetadataField",
    metadata_field="metadataField",
    primary_key_field="primaryKeyField",
    text_field="textField",
    vector_field="vectorField"
)

Attributes

custom_metadata_field

Provide a name for the universal metadata field where Amazon Bedrock will store any custom metadata from your data source.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsfieldmapping.html#cfn-bedrock-knowledgebase-rdsfieldmapping-custommetadatafield

metadata_field

The name of the field in which Amazon Bedrock stores metadata about the vector store.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsfieldmapping.html#cfn-bedrock-knowledgebase-rdsfieldmapping-metadatafield

primary_key_field

The name of the field in which Amazon Bedrock stores the ID for each entry.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsfieldmapping.html#cfn-bedrock-knowledgebase-rdsfieldmapping-primarykeyfield

text_field

The name of the field in which Amazon Bedrock stores the raw text from your data.

The text is split according to the chunking strategy you choose.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsfieldmapping.html#cfn-bedrock-knowledgebase-rdsfieldmapping-textfield

vector_field

The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-rdsfieldmapping.html#cfn-bedrock-knowledgebase-rdsfieldmapping-vectorfield

RedshiftConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftConfigurationProperty(*, query_engine_configuration=None, query_generation_configuration=None, storage_configurations=None)

Bases: object

Contains configurations for an Amazon Redshift database.

For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.

Parameters:

• query_engine_configuration (Union[IResolvable, RedshiftQueryEngineConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for an Amazon Redshift query engine.

• query_generation_configuration (Union[IResolvable, QueryGenerationConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for generating queries.

• storage_configurations (Union[IResolvable, Sequence[Union[IResolvable, RedshiftQueryEngineStorageConfigurationProperty, Dict[str, Any]]], None]) – Specifies configurations for Amazon Redshift database storage.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftConfigurationProperty(
    query_engine_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineConfigurationProperty(
        provisioned_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(
            auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
                database_user="databaseUser",
                type="type",
                username_password_secret_arn="usernamePasswordSecretArn"
            ),
            cluster_identifier="clusterIdentifier"
        ),
        serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(
            auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
                type="type",
                username_password_secret_arn="usernamePasswordSecretArn"
            ),
            workgroup_arn="workgroupArn"
        ),
        type="type"
    ),
    query_generation_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationConfigurationProperty(
        execution_timeout_seconds=123,
        generation_context=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationContextProperty(
            curated_queries=[bedrock_mixins.CfnKnowledgeBasePropsMixin.CuratedQueryProperty(
                natural_language="naturalLanguage",
                sql="sql"
            )],
            tables=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(
                columns=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
                    description="description",
                    inclusion="inclusion",
                    name="name"
                )],
                description="description",
                inclusion="inclusion",
                name="name"
            )]
        )
    ),
    storage_configurations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineStorageConfigurationProperty(
        aws_data_catalog_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(
            table_names=["tableNames"]
        ),
        redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(
            database_name="databaseName"
        ),
        type="type"
    )]
)

Attributes

query_engine_configuration

Specifies configurations for an Amazon Redshift query engine.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftconfiguration.html#cfn-bedrock-knowledgebase-redshiftconfiguration-queryengineconfiguration

query_generation_configuration

Specifies configurations for generating queries.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftconfiguration.html#cfn-bedrock-knowledgebase-redshiftconfiguration-querygenerationconfiguration

storage_configurations

Specifies configurations for Amazon Redshift database storage.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftconfiguration.html#cfn-bedrock-knowledgebase-redshiftconfiguration-storageconfigurations

RedshiftProvisionedAuthConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(*, database_user=None, type=None, username_password_secret_arn=None)

Bases: object

Contains configurations for authentication to an Amazon Redshift provisioned data warehouse.

Specify the type of authentication to use in the type field and include the corresponding field. If you specify IAM authentication, you don’t need to include another field.

Parameters:

• database_user (Optional[str]) – The database username for authentication to an Amazon Redshift provisioned data warehouse.

• type (Optional[str]) – The type of authentication to use.

• username_password_secret_arn (Optional[str]) – The ARN of an Secrets Manager secret for authentication.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedauthconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_provisioned_auth_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
    database_user="databaseUser",
    type="type",
    username_password_secret_arn="usernamePasswordSecretArn"
)

Attributes

database_user

The database username for authentication to an Amazon Redshift provisioned data warehouse.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedauthconfiguration.html#cfn-bedrock-knowledgebase-redshiftprovisionedauthconfiguration-databaseuser

type

The type of authentication to use.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedauthconfiguration.html#cfn-bedrock-knowledgebase-redshiftprovisionedauthconfiguration-type

username_password_secret_arn

The ARN of an Secrets Manager secret for authentication.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedauthconfiguration.html#cfn-bedrock-knowledgebase-redshiftprovisionedauthconfiguration-usernamepasswordsecretarn

RedshiftProvisionedConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(*, auth_configuration=None, cluster_identifier=None)

Bases: object

Contains configurations for a provisioned Amazon Redshift query engine.

Parameters:

• auth_configuration (Union[IResolvable, RedshiftProvisionedAuthConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for authentication to Amazon Redshift.

• cluster_identifier (Optional[str]) – The ID of the Amazon Redshift cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_provisioned_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(
    auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
        database_user="databaseUser",
        type="type",
        username_password_secret_arn="usernamePasswordSecretArn"
    ),
    cluster_identifier="clusterIdentifier"
)

Attributes

auth_configuration

Specifies configurations for authentication to Amazon Redshift.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedconfiguration.html#cfn-bedrock-knowledgebase-redshiftprovisionedconfiguration-authconfiguration

cluster_identifier

The ID of the Amazon Redshift cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftprovisionedconfiguration.html#cfn-bedrock-knowledgebase-redshiftprovisionedconfiguration-clusteridentifier

RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(*, table_names=None)

Bases: object

Contains configurations for storage in AWS Glue Data Catalog.

Parameters:

table_names (Optional[Sequence[str]]) – A list of names of the tables to use.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineawsdatacatalogstorageconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_query_engine_aws_data_catalog_storage_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(
    table_names=["tableNames"]
)

Attributes

table_names

A list of names of the tables to use.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineawsdatacatalogstorageconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryengineawsdatacatalogstorageconfiguration-tablenames

RedshiftQueryEngineConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftQueryEngineConfigurationProperty(*, provisioned_configuration=None, serverless_configuration=None, type=None)

Bases: object

Contains configurations for an Amazon Redshift query engine.

Specify the type of query engine in type and include the corresponding field. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.

Parameters:

• provisioned_configuration (Union[IResolvable, RedshiftProvisionedConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for a provisioned Amazon Redshift query engine.

• serverless_configuration (Union[IResolvable, RedshiftServerlessConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for a serverless Amazon Redshift query engine.

• type (Optional[str]) – The type of query engine.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_query_engine_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineConfigurationProperty(
    provisioned_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(
        auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
            database_user="databaseUser",
            type="type",
            username_password_secret_arn="usernamePasswordSecretArn"
        ),
        cluster_identifier="clusterIdentifier"
    ),
    serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(
        auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
            type="type",
            username_password_secret_arn="usernamePasswordSecretArn"
        ),
        workgroup_arn="workgroupArn"
    ),
    type="type"
)

Attributes

provisioned_configuration

Specifies configurations for a provisioned Amazon Redshift query engine.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryengineconfiguration-provisionedconfiguration

serverless_configuration

Specifies configurations for a serverless Amazon Redshift query engine.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryengineconfiguration-serverlessconfiguration

type

The type of query engine.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryengineconfiguration-type

RedshiftQueryEngineRedshiftStorageConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(*, database_name=None)

Bases: object

Contains configurations for storage in Amazon Redshift.

Parameters:

database_name (Optional[str]) – The name of the Amazon Redshift database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineredshiftstorageconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_query_engine_redshift_storage_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(
    database_name="databaseName"
)

Attributes

database_name

The name of the Amazon Redshift database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryengineredshiftstorageconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryengineredshiftstorageconfiguration-databasename

RedshiftQueryEngineStorageConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftQueryEngineStorageConfigurationProperty(*, aws_data_catalog_configuration=None, redshift_configuration=None, type=None)

Bases: object

Contains configurations for Amazon Redshift data storage.

Specify the data storage service to use in the type field and include the corresponding field. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.

Parameters:

• aws_data_catalog_configuration (Union[IResolvable, RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for storage in AWS Glue Data Catalog.

• redshift_configuration (Union[IResolvable, RedshiftQueryEngineRedshiftStorageConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for storage in Amazon Redshift.

• type (Optional[str]) – The data storage service to use.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_query_engine_storage_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineStorageConfigurationProperty(
    aws_data_catalog_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(
        table_names=["tableNames"]
    ),
    redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(
        database_name="databaseName"
    ),
    type="type"
)

Attributes

aws_data_catalog_configuration

Specifies configurations for storage in AWS Glue Data Catalog.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration-awsdatacatalogconfiguration

redshift_configuration

Specifies configurations for storage in Amazon Redshift.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration-redshiftconfiguration

type

The data storage service to use.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration.html#cfn-bedrock-knowledgebase-redshiftqueryenginestorageconfiguration-type

RedshiftServerlessAuthConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(*, type=None, username_password_secret_arn=None)

Bases: object

Specifies configurations for authentication to a Redshift Serverless.

Specify the type of authentication to use in the type field and include the corresponding field. If you specify IAM authentication, you don’t need to include another field.

Parameters:

• type (Optional[str]) – The type of authentication to use.

• username_password_secret_arn (Optional[str]) – The ARN of an Secrets Manager secret for authentication.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftserverlessauthconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_serverless_auth_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
    type="type",
    username_password_secret_arn="usernamePasswordSecretArn"
)

Attributes

type

The type of authentication to use.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftserverlessauthconfiguration.html#cfn-bedrock-knowledgebase-redshiftserverlessauthconfiguration-type

username_password_secret_arn

The ARN of an Secrets Manager secret for authentication.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftserverlessauthconfiguration.html#cfn-bedrock-knowledgebase-redshiftserverlessauthconfiguration-usernamepasswordsecretarn

RedshiftServerlessConfigurationProperty

class CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(*, auth_configuration=None, workgroup_arn=None)

Bases: object

Contains configurations for authentication to Amazon Redshift Serverless.

Parameters:

• auth_configuration (Union[IResolvable, RedshiftServerlessAuthConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for authentication to an Amazon Redshift provisioned data warehouse.

• workgroup_arn (Optional[str]) – The ARN of the Amazon Redshift workgroup.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftserverlessconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

redshift_serverless_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(
    auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
        type="type",
        username_password_secret_arn="usernamePasswordSecretArn"
    ),
    workgroup_arn="workgroupArn"
)

Attributes

auth_configuration

Specifies configurations for authentication to an Amazon Redshift provisioned data warehouse.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftserverlessconfiguration.html#cfn-bedrock-knowledgebase-redshiftserverlessconfiguration-authconfiguration

workgroup_arn

The ARN of the Amazon Redshift workgroup.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-redshiftserverlessconfiguration.html#cfn-bedrock-knowledgebase-redshiftserverlessconfiguration-workgrouparn

S3LocationProperty

class CfnKnowledgeBasePropsMixin.S3LocationProperty(*, uri=None)

Bases: object

A storage location in an Amazon S3 bucket.

Parameters:

uri (Optional[str]) – An object URI starting with s3:// .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-s3location.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

s3_location_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.S3LocationProperty(
    uri="uri"
)

Attributes

uri

An object URI starting with s3:// .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-s3location.html#cfn-bedrock-knowledgebase-s3location-uri

S3VectorsConfigurationProperty

class CfnKnowledgeBasePropsMixin.S3VectorsConfigurationProperty(*, index_arn=None, index_name=None, vector_bucket_arn=None)

Bases: object

Contains the storage configuration of the knowledge base for S3 vectors.

Parameters:

• index_arn (Optional[str]) – The Amazon Resource Name (ARN) of the vector index used for the knowledge base. This ARN identifies the specific vector index resource within Amazon Bedrock.

• index_name (Optional[str]) – The name of the vector index used for the knowledge base. This name identifies the vector index within the Amazon Bedrock service.

• vector_bucket_arn (Optional[str]) – The Amazon Resource Name (ARN) of the S3 bucket where vector embeddings are stored. This bucket contains the vector data used by the knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-s3vectorsconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

s3_vectors_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.S3VectorsConfigurationProperty(
    index_arn="indexArn",
    index_name="indexName",
    vector_bucket_arn="vectorBucketArn"
)

Attributes

index_arn

The Amazon Resource Name (ARN) of the vector index used for the knowledge base.

This ARN identifies the specific vector index resource within Amazon Bedrock.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-s3vectorsconfiguration.html#cfn-bedrock-knowledgebase-s3vectorsconfiguration-indexarn

index_name

The name of the vector index used for the knowledge base.

This name identifies the vector index within the Amazon Bedrock service.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-s3vectorsconfiguration.html#cfn-bedrock-knowledgebase-s3vectorsconfiguration-indexname

vector_bucket_arn

The Amazon Resource Name (ARN) of the S3 bucket where vector embeddings are stored.

This bucket contains the vector data used by the knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-s3vectorsconfiguration.html#cfn-bedrock-knowledgebase-s3vectorsconfiguration-vectorbucketarn

SqlKnowledgeBaseConfigurationProperty

class CfnKnowledgeBasePropsMixin.SqlKnowledgeBaseConfigurationProperty(*, redshift_configuration=None, type=None)

Bases: object

Contains configurations for a knowledge base connected to an SQL database.

Specify the SQL database type in the type field and include the corresponding field. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.

Parameters:

• redshift_configuration (Union[IResolvable, RedshiftConfigurationProperty, Dict[str, Any], None]) – Specifies configurations for a knowledge base connected to an Amazon Redshift database.

• type (Optional[str]) – The type of SQL database to connect to the knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-sqlknowledgebaseconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

sql_knowledge_base_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.SqlKnowledgeBaseConfigurationProperty(
    redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftConfigurationProperty(
        query_engine_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineConfigurationProperty(
            provisioned_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedConfigurationProperty(
                auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftProvisionedAuthConfigurationProperty(
                    database_user="databaseUser",
                    type="type",
                    username_password_secret_arn="usernamePasswordSecretArn"
                ),
                cluster_identifier="clusterIdentifier"
            ),
            serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessConfigurationProperty(
                auth_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftServerlessAuthConfigurationProperty(
                    type="type",
                    username_password_secret_arn="usernamePasswordSecretArn"
                ),
                workgroup_arn="workgroupArn"
            ),
            type="type"
        ),
        query_generation_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationConfigurationProperty(
            execution_timeout_seconds=123,
            generation_context=bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationContextProperty(
                curated_queries=[bedrock_mixins.CfnKnowledgeBasePropsMixin.CuratedQueryProperty(
                    natural_language="naturalLanguage",
                    sql="sql"
                )],
                tables=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationTableProperty(
                    columns=[bedrock_mixins.CfnKnowledgeBasePropsMixin.QueryGenerationColumnProperty(
                        description="description",
                        inclusion="inclusion",
                        name="name"
                    )],
                    description="description",
                    inclusion="inclusion",
                    name="name"
                )]
            )
        ),
        storage_configurations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineStorageConfigurationProperty(
            aws_data_catalog_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineAwsDataCatalogStorageConfigurationProperty(
                table_names=["tableNames"]
            ),
            redshift_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RedshiftQueryEngineRedshiftStorageConfigurationProperty(
                database_name="databaseName"
            ),
            type="type"
        )]
    ),
    type="type"
)

Attributes

redshift_configuration

Specifies configurations for a knowledge base connected to an Amazon Redshift database.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-sqlknowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-sqlknowledgebaseconfiguration-redshiftconfiguration

type

The type of SQL database to connect to the knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-sqlknowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-sqlknowledgebaseconfiguration-type

StorageConfigurationProperty

class CfnKnowledgeBasePropsMixin.StorageConfigurationProperty(*, mongo_db_atlas_configuration=None, neptune_analytics_configuration=None, opensearch_managed_cluster_configuration=None, opensearch_serverless_configuration=None, pinecone_configuration=None, rds_configuration=None, s3_vectors_configuration=None, type=None)

Bases: object

Contains the storage configuration of the knowledge base.

Parameters:

• mongo_db_atlas_configuration (Union[IResolvable, MongoDbAtlasConfigurationProperty, Dict[str, Any], None]) – Contains the storage configuration of the knowledge base in MongoDB Atlas.

• neptune_analytics_configuration (Union[IResolvable, NeptuneAnalyticsConfigurationProperty, Dict[str, Any], None]) – Contains details about the Neptune Analytics configuration of the knowledge base in Amazon Neptune. For more information, see Create a vector index in Amazon Neptune Analytics. .

• opensearch_managed_cluster_configuration (Union[IResolvable, OpenSearchManagedClusterConfigurationProperty, Dict[str, Any], None]) –

  Contains details about the storage configuration of the knowledge base in OpenSearch Managed Cluster. For more information, see Create a vector index in Amazon OpenSearch Service .

• opensearch_serverless_configuration (Union[IResolvable, OpenSearchServerlessConfigurationProperty, Dict[str, Any], None]) – Contains the storage configuration of the knowledge base in Amazon OpenSearch Service.

• pinecone_configuration (Union[IResolvable, PineconeConfigurationProperty, Dict[str, Any], None]) – Contains the storage configuration of the knowledge base in Pinecone.

• rds_configuration (Union[IResolvable, RdsConfigurationProperty, Dict[str, Any], None]) –

  Contains details about the storage configuration of the knowledge base in Amazon RDS. For more information, see Create a vector index in Amazon RDS .

• s3_vectors_configuration (Union[IResolvable, S3VectorsConfigurationProperty, Dict[str, Any], None]) – The configuration settings for storing knowledge base data using S3 vectors. This includes vector index information and S3 bucket details for vector storage.

• type (Optional[str]) – The vector store service in which the knowledge base is stored.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

storage_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.StorageConfigurationProperty(
    mongo_db_atlas_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasConfigurationProperty(
        collection_name="collectionName",
        credentials_secret_arn="credentialsSecretArn",
        database_name="databaseName",
        endpoint="endpoint",
        endpoint_service_name="endpointServiceName",
        field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.MongoDbAtlasFieldMappingProperty(
            metadata_field="metadataField",
            text_field="textField",
            vector_field="vectorField"
        ),
        text_index_name="textIndexName",
        vector_index_name="vectorIndexName"
    ),
    neptune_analytics_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsConfigurationProperty(
        field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.NeptuneAnalyticsFieldMappingProperty(
            metadata_field="metadataField",
            text_field="textField"
        ),
        graph_arn="graphArn"
    ),
    opensearch_managed_cluster_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterConfigurationProperty(
        domain_arn="domainArn",
        domain_endpoint="domainEndpoint",
        field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchManagedClusterFieldMappingProperty(
            metadata_field="metadataField",
            text_field="textField",
            vector_field="vectorField"
        ),
        vector_index_name="vectorIndexName"
    ),
    opensearch_serverless_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessConfigurationProperty(
        collection_arn="collectionArn",
        field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.OpenSearchServerlessFieldMappingProperty(
            metadata_field="metadataField",
            text_field="textField",
            vector_field="vectorField"
        ),
        vector_index_name="vectorIndexName"
    ),
    pinecone_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeConfigurationProperty(
        connection_string="connectionString",
        credentials_secret_arn="credentialsSecretArn",
        field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.PineconeFieldMappingProperty(
            metadata_field="metadataField",
            text_field="textField"
        ),
        namespace="namespace"
    ),
    rds_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsConfigurationProperty(
        credentials_secret_arn="credentialsSecretArn",
        database_name="databaseName",
        field_mapping=bedrock_mixins.CfnKnowledgeBasePropsMixin.RdsFieldMappingProperty(
            custom_metadata_field="customMetadataField",
            metadata_field="metadataField",
            primary_key_field="primaryKeyField",
            text_field="textField",
            vector_field="vectorField"
        ),
        resource_arn="resourceArn",
        table_name="tableName"
    ),
    s3_vectors_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3VectorsConfigurationProperty(
        index_arn="indexArn",
        index_name="indexName",
        vector_bucket_arn="vectorBucketArn"
    ),
    type="type"
)

Attributes

mongo_db_atlas_configuration

Contains the storage configuration of the knowledge base in MongoDB Atlas.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-mongodbatlasconfiguration

neptune_analytics_configuration

Contains details about the Neptune Analytics configuration of the knowledge base in Amazon Neptune.

For more information, see Create a vector index in Amazon Neptune Analytics. .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-neptuneanalyticsconfiguration

opensearch_managed_cluster_configuration

Contains details about the storage configuration of the knowledge base in OpenSearch Managed Cluster.

For more information, see Create a vector index in Amazon OpenSearch Service .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-opensearchmanagedclusterconfiguration

opensearch_serverless_configuration

Contains the storage configuration of the knowledge base in Amazon OpenSearch Service.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-opensearchserverlessconfiguration

pinecone_configuration

Contains the storage configuration of the knowledge base in Pinecone.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-pineconeconfiguration

rds_configuration

Contains details about the storage configuration of the knowledge base in Amazon RDS.

For more information, see Create a vector index in Amazon RDS .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-rdsconfiguration

s3_vectors_configuration

The configuration settings for storing knowledge base data using S3 vectors.

This includes vector index information and S3 bucket details for vector storage.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-s3vectorsconfiguration

type

The vector store service in which the knowledge base is stored.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-storageconfiguration.html#cfn-bedrock-knowledgebase-storageconfiguration-type

SupplementalDataStorageConfigurationProperty

class CfnKnowledgeBasePropsMixin.SupplementalDataStorageConfigurationProperty(*, supplemental_data_storage_locations=None)

Bases: object

Specifies configurations for the storage location of the images extracted from multimodal documents in your data source.

These images can be retrieved and returned to the end user.

Parameters:

supplemental_data_storage_locations (Union[IResolvable, Sequence[Union[IResolvable, SupplementalDataStorageLocationProperty, Dict[str, Any]]], None]) – List of supplemental data storage locations.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-supplementaldatastorageconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

supplemental_data_storage_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageConfigurationProperty(
    supplemental_data_storage_locations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageLocationProperty(
        s3_location=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3LocationProperty(
            uri="uri"
        ),
        supplemental_data_storage_location_type="supplementalDataStorageLocationType"
    )]
)

Attributes

supplemental_data_storage_locations

List of supplemental data storage locations.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-supplementaldatastorageconfiguration.html#cfn-bedrock-knowledgebase-supplementaldatastorageconfiguration-supplementaldatastoragelocations

SupplementalDataStorageLocationProperty

class CfnKnowledgeBasePropsMixin.SupplementalDataStorageLocationProperty(*, s3_location=None, supplemental_data_storage_location_type=None)

Bases: object

Contains information about a storage location for images extracted from multimodal documents in your data source.

Parameters:

• s3_location (Union[IResolvable, S3LocationProperty, Dict[str, Any], None]) – Contains information about the Amazon S3 location for the extracted images.

• supplemental_data_storage_location_type (Optional[str]) – Supplemental data storage location type.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-supplementaldatastoragelocation.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

supplemental_data_storage_location_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageLocationProperty(
    s3_location=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3LocationProperty(
        uri="uri"
    ),
    supplemental_data_storage_location_type="supplementalDataStorageLocationType"
)

Attributes

s3_location

Contains information about the Amazon S3 location for the extracted images.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-supplementaldatastoragelocation.html#cfn-bedrock-knowledgebase-supplementaldatastoragelocation-s3location

supplemental_data_storage_location_type

Supplemental data storage location type.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-supplementaldatastoragelocation.html#cfn-bedrock-knowledgebase-supplementaldatastoragelocation-supplementaldatastoragelocationtype

VectorKnowledgeBaseConfigurationProperty

class CfnKnowledgeBasePropsMixin.VectorKnowledgeBaseConfigurationProperty(*, embedding_model_arn=None, embedding_model_configuration=None, supplemental_data_storage_configuration=None)

Bases: object

Contains details about the model used to create vector embeddings for the knowledge base.

Parameters:

• embedding_model_arn (Optional[str]) – The Amazon Resource Name (ARN) of the model used to create vector embeddings for the knowledge base.

• embedding_model_configuration (Union[IResolvable, EmbeddingModelConfigurationProperty, Dict[str, Any], None]) – The embeddings model configuration details for the vector model used in Knowledge Base.

• supplemental_data_storage_configuration (Union[IResolvable, SupplementalDataStorageConfigurationProperty, Dict[str, Any], None]) – If you include multimodal data from your data source, use this object to specify configurations for the storage location of the images extracted from your documents. These images can be retrieved and returned to the end user. They can also be used in generation when using RetrieveAndGenerate .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-vectorknowledgebaseconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_bedrock import mixins as bedrock_mixins

vector_knowledge_base_configuration_property = bedrock_mixins.CfnKnowledgeBasePropsMixin.VectorKnowledgeBaseConfigurationProperty(
    embedding_model_arn="embeddingModelArn",
    embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.EmbeddingModelConfigurationProperty(
        bedrock_embedding_model_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.BedrockEmbeddingModelConfigurationProperty(
            dimensions=123,
            embedding_data_type="embeddingDataType"
        )
    ),
    supplemental_data_storage_configuration=bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageConfigurationProperty(
        supplemental_data_storage_locations=[bedrock_mixins.CfnKnowledgeBasePropsMixin.SupplementalDataStorageLocationProperty(
            s3_location=bedrock_mixins.CfnKnowledgeBasePropsMixin.S3LocationProperty(
                uri="uri"
            ),
            supplemental_data_storage_location_type="supplementalDataStorageLocationType"
        )]
    )
)

Attributes

embedding_model_arn

The Amazon Resource Name (ARN) of the model used to create vector embeddings for the knowledge base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-vectorknowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-vectorknowledgebaseconfiguration-embeddingmodelarn

embedding_model_configuration

The embeddings model configuration details for the vector model used in Knowledge Base.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-vectorknowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-vectorknowledgebaseconfiguration-embeddingmodelconfiguration

supplemental_data_storage_configuration

If you include multimodal data from your data source, use this object to specify configurations for the storage location of the images extracted from your documents.

These images can be retrieved and returned to the end user. They can also be used in generation when using RetrieveAndGenerate .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-knowledgebase-vectorknowledgebaseconfiguration.html#cfn-bedrock-knowledgebase-vectorknowledgebaseconfiguration-supplementaldatastorageconfiguration