@aws-cdk/aws-bedrock-alpha.BedrockFoundationModelProps

Experimental

@aws-cdk/aws-bedrock-alpha is an experimental (alpha) package: its API may change in any release, without a major version bump.

BedrockFoundationModelProps Struct

Properties for configuring a Bedrock Foundation Model.

These properties define the model's capabilities and supported features.

BedrockFoundationModelProps

used as props by

• BedrockFoundationModel

Stability

Experimental

Source

bedrock/models.ts

Type last changed

v2.274.0-alpha.0 · 21 Oct 2026

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import * as bedrock_alpha from '@aws-cdk/aws-bedrock-alpha';
const bedrockFoundationModelProps: bedrock_alpha.BedrockFoundationModelProps = {
  legacy: false,
  optimizedForAgents: false,
  supportedVectorType: [bedrock_alpha.VectorType.FLOATING_POINT],
  supportsAgents: false,
  supportsConfigurableDimensions: false,
  supportsCrossRegion: false,
  supportsKnowledgeBase: false,
  vectorDimensions: 123,
};

Properties

legacybooleanlegacyboollegacyBooleanLegacyboolLegacy*bool= false#

https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle.html A version is marked Legacy when there is a more recent version which provides superior performance. Amazon Bedrock sets an EOL date for Legacy versions.

optimizedForAgentsbooleanoptimized_for_agentsbooloptimizedForAgentsBooleanOptimizedForAgentsboolOptimizedForAgents*bool= false#

Currently, some of the offered models are optimized with prompts/parsers fine-tuned for integrating with the agents architecture.

When true, the model has been specifically optimized for agent interactions.

supportedVectorTypeVectorType[]supported_vector_typetyping.List[VectorType]supportedVectorTypeList<VectorType>SupportedVectorTypeVectorType[]SupportedVectorType*[]VectorType= undefined#

Embeddings models have different supported vector types.

Defines whether the model supports floating-point or binary vectors.

supportsAgentsbooleansupports_agentsboolsupportsAgentsBooleanSupportsAgentsboolSupportsAgents*bool= false#

Bedrock Agents can use this model.

When true, the model can be used with Bedrock Agents for automated task execution.

supportsConfigurableDimensionsbooleansupports_configurable_dimensionsboolsupportsConfigurableDimensionsBooleanSupportsConfigurableDimensionsboolSupportsConfigurableDimensions*bool= false#

Whether the number of vector dimensions can be chosen when the model is used by a knowledge base.

Only applicable for embedding models. When true, vectorDimensions is passed to the knowledge base; when false, the model's dimension is fixed and vectorDimensions is informational only.

supportsCrossRegionbooleansupports_cross_regionboolsupportsCrossRegionBooleanSupportsCrossRegionboolSupportsCrossRegion*bool= false#

Can be used with a Cross-Region Inference Profile.

When true, the model supports inference across different AWS regions.

supportsKnowledgeBasebooleansupports_knowledge_baseboolsupportsKnowledgeBaseBooleanSupportsKnowledgeBaseboolSupportsKnowledgeBase*bool= false#

Bedrock Knowledge Base can use this model.

When true, the model can be used for knowledge base operations.

vectorDimensionsnumbervector_dimensionsint | floatvectorDimensionsNumberVectorDimensionsdoubleVectorDimensions*float64= undefined#

Embedding models have different vector dimensions.

Only applicable for embedding models. Defines the dimensionality of the vector embeddings.