AWS::Bedrock::KnowledgeBase RdsFieldMapping - AWS CloudFormation
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AWS::Bedrock::KnowledgeBase RdsFieldMapping

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

Syntax

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

JSON

{ "CustomMetadataField" : String, "MetadataField" : String, "PrimaryKeyField" : String, "TextField" : String, "VectorField" : String }

YAML

CustomMetadataField: String MetadataField: String PrimaryKeyField: String TextField: String VectorField: String

Properties

CustomMetadataField

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

Required: No

Type: String

Pattern: ^[a-zA-Z0-9_\-]+$

Maximum: 63

Update requires: Replacement

MetadataField

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

Required: Yes

Type: String

Pattern: ^[a-zA-Z0-9_\-]+$

Maximum: 63

Update requires: Replacement

PrimaryKeyField

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

Required: Yes

Type: String

Pattern: ^[a-zA-Z0-9_\-]+$

Maximum: 63

Update requires: Replacement

TextField

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.

Required: Yes

Type: String

Pattern: ^[a-zA-Z0-9_\-]+$

Maximum: 63

Update requires: Replacement

VectorField

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

Required: Yes

Type: String

Pattern: ^[a-zA-Z0-9_\-]+$

Maximum: 63

Update requires: Replacement