@aws-cdk/aws-bedrock-agentcore-alpha.MemoryStrategy

Experimental

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

MemoryStrategy Class

Factory class for creating memory strategies If you need long-term memory for context recall across sessions, you can setup memory extraction strategies to extract the relevant memory from the raw events.

Use built-in strategies for quick setup, use built-in strategies with override to specify models and prompt templates.

Source

lib/memory/memory-strategy.ts

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import * as bedrock_agentcore_alpha from '@aws-cdk/aws-bedrock-agentcore-alpha';
const memoryStrategy = new bedrock_agentcore_alpha.MemoryStrategy();

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
import aws_cdk.aws_bedrock_agentcore_alpha as bedrock_agentcore_alpha

memory_strategy = bedrock_agentcore_alpha.MemoryStrategy()

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import software.amazon.awscdk.services.bedrock.agentcore.alpha.*;

MemoryStrategy memoryStrategy = new MemoryStrategy();

// Install: dotnet add package Amazon.CDK.AWS.Bedrock.Agentcore.Alpha
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
using Amazon.CDK.AWS.Bedrock.Agentcore.Alpha;

var memoryStrategy = new MemoryStrategy();

// Install: go get github.com/aws/aws-cdk-go/awsbedrockagentcorealpha/v2
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import bedrock_agentcore_alpha "github.com/aws/aws-cdk-go/awsbedrockagentcorealpha"

memoryStrategy := bedrock_agentcore_alpha.NewMemoryStrategy()

Initializer

new MemoryStrategy()

MemoryStrategy()

new MemoryStrategy()

new MemoryStrategy()

NewMemoryStrategy()

Methods

usingBuiltInEpisodic(): ManagedMemoryStrategy@staticmethod def using_built_in_episodic() -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingBuiltInEpisodic()public static ManagedMemoryStrategy UsingBuiltInEpisodic()func UsingBuiltInEpisodic() ManagedMemoryStrategystatic#

Default strategies for organizing and extracting memory data, each optimized for specific use cases.

notes · returns

Captures meaningful slices of user and system interactions, preserve them into compact records after summarizing. Extracted memory example: User first asked about pricing on Monday, then requested feature comparison on Tuesday, finally made purchase decision on Wednesday.

Returns: A ManagedMemoryStrategy.

usingBuiltInSemantic(): ManagedMemoryStrategy@staticmethod def using_built_in_semantic() -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingBuiltInSemantic()public static ManagedMemoryStrategy UsingBuiltInSemantic()func UsingBuiltInSemantic() ManagedMemoryStrategystatic#

Default strategies for organizing and extracting memory data, each optimized for specific use cases.

notes · returns

Distills general facts, concepts, and underlying meanings from raw conversational data, presenting the information in a context-independent format. Extracted memory example: In-context learning = task-solving via examples, no training needed.

Returns: A ManagedMemoryStrategy.

usingBuiltInSummarization(): ManagedMemoryStrategy@staticmethod def using_built_in_summarization() -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingBuiltInSummarization()public static ManagedMemoryStrategy UsingBuiltInSummarization()func UsingBuiltInSummarization() ManagedMemoryStrategystatic#

Default strategies for organizing and extracting memory data, each optimized for specific use cases.

This strategy compresses conversations into concise overviews, preserving essential context and key insights for quick recall. Extracted memory example: Users confused by cloud setup during onboarding.

returns

Returns: A ManagedMemoryStrategy.

usingBuiltInUserPreference(): ManagedMemoryStrategy@staticmethod def using_built_in_user_preference() -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingBuiltInUserPreference()public static ManagedMemoryStrategy UsingBuiltInUserPreference()func UsingBuiltInUserPreference() ManagedMemoryStrategystatic#

Default strategies for organizing and extracting memory data, each optimized for specific use cases.

Captures individual preferences, interaction patterns, and personalized settings to enhance future experiences. Extracted memory example: User needs clear guidance on cloud storage account connection during onboarding.

returns

Returns: A ManagedMemoryStrategy.

usingEpisodic(config: ManagedStrategyProps): ManagedMemoryStrategy@staticmethod def using_episodic(config: ManagedStrategyProps) -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingEpisodic(ManagedStrategyProps config)public static ManagedMemoryStrategy UsingEpisodic(ManagedStrategyProps config)func UsingEpisodic(Config ManagedStrategyProps) ManagedMemoryStrategystatic#

Creates an episodic memory strategy with custom configuration.

notes · 1 parameter · returns

Captures meaningful slices of user and system interactions, preserve them into compact records after summarizing. Extracted memory example: User first asked about pricing on Monday, then requested feature comparison on Tuesday, finally made purchase decision on Wednesday.

Parameters

• configconfigconfigconfigConfig — - The configuration for the episodic memory strategy.

Returns: A ManagedMemoryStrategy.

usingSelfManaged(config: SelfManagedStrategyProps): SelfManagedMemoryStrategy@staticmethod def using_self_managed(config: SelfManagedStrategyProps) -> SelfManagedMemoryStrategypublic static SelfManagedMemoryStrategy usingSelfManaged(SelfManagedStrategyProps config)public static SelfManagedMemoryStrategy UsingSelfManaged(SelfManagedStrategyProps config)func UsingSelfManaged(Config SelfManagedStrategyProps) SelfManagedMemoryStrategystatic#

Creates a self-managed memory strategy.

A self-managed strategy gives you complete control over your memory extraction and consolidation pipelines.

1 parameter · returns

Parameters

• configconfigconfigconfigConfig — - The configuration for the self-managed memory strategy.

Returns: A SelfManagedMemoryStrategy.

usingSemantic(config: ManagedStrategyProps): ManagedMemoryStrategy@staticmethod def using_semantic(config: ManagedStrategyProps) -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingSemantic(ManagedStrategyProps config)public static ManagedMemoryStrategy UsingSemantic(ManagedStrategyProps config)func UsingSemantic(Config ManagedStrategyProps) ManagedMemoryStrategystatic#

Creates a semantic memory strategy with custom configuration.

notes · 1 parameter · returns

Distills general facts, concepts, and underlying meanings from raw conversational data, presenting the information in a context-independent format. Extracted memory example: In-context learning = task-solving via examples, no training needed.

Parameters

• configconfigconfigconfigConfig — - The configuration for the semantic memory strategy.

Returns: A ManagedMemoryStrategy.

usingSummarization(config: ManagedStrategyProps): ManagedMemoryStrategy@staticmethod def using_summarization(config: ManagedStrategyProps) -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingSummarization(ManagedStrategyProps config)public static ManagedMemoryStrategy UsingSummarization(ManagedStrategyProps config)func UsingSummarization(Config ManagedStrategyProps) ManagedMemoryStrategystatic#

Creates a summarization memory strategy with custom configuration.

This strategy compresses conversations into concise overviews, preserving essential context and key insights for quick recall. Extracted memory example: Users confused by cloud setup during onboarding.

1 parameter · returns

Parameters

• configconfigconfigconfigConfig — - The configuration for the summarization memory strategy.

Returns: A ManagedMemoryStrategy.

usingUserPreference(config: ManagedStrategyProps): ManagedMemoryStrategy@staticmethod def using_user_preference(config: ManagedStrategyProps) -> ManagedMemoryStrategypublic static ManagedMemoryStrategy usingUserPreference(ManagedStrategyProps config)public static ManagedMemoryStrategy UsingUserPreference(ManagedStrategyProps config)func UsingUserPreference(Config ManagedStrategyProps) ManagedMemoryStrategystatic#

Creates a user preference memory strategy with custom configuration.

Captures individual preferences, interaction patterns, and personalized settings to enhance future experiences. Extracted memory example: User needs clear guidance on cloud storage account connection during onboarding.

1 parameter · returns

Parameters

• configconfigconfigconfigConfig — - The configuration for the user preference memory strategy.

Returns: A ManagedMemoryStrategy.