/**
 *  Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
 *
 *  Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
 *  with the License. A copy of the License is located at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 *  or in the 'license' file accompanying this file. This file is distributed on an 'AS IS' BASIS, WITHOUT WARRANTIES
 *  OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions
 *  and limitations under the License.
 */
import type { ManagedStrategyProps } from './strategies/managed-strategy';
import { ManagedMemoryStrategy } from './strategies/managed-strategy';
import type { SelfManagedStrategyProps } from './strategies/self-managed-strategy';
import { SelfManagedMemoryStrategy } from './strategies/self-managed-strategy';
import type * as bedrockagentcore from '../../../aws-bedrockagentcore';
import type * as iam from '../../../aws-iam';
/******************************************************************************
 *                              CONSTANTS
 *****************************************************************************/
/**
 * Minimum length for memory strategy name
 * @internal
 */
export declare const MEMORY_NAME_MIN_LENGTH = 1;
/**
 * Maximum length for memory strategy name
 * @internal
 */
export declare const MEMORY_NAME_MAX_LENGTH = 48;
/**
 * Long-term memory extraction strategy types.
 */
export declare enum MemoryStrategyType {
    /**
     * Summarization strategy - extracts concise summaries to preserve critical context and key insights
     */
    SUMMARIZATION = "SUMMARIZATION",
    /**
     * Semantic memory strategy - extracts general factual knowledge, concepts and meanings from raw conversations
     * using vector embeddings for similarity search.
     */
    SEMANTIC = "SEMANTIC",
    /**
     * User preferences strategy - extracts user behavior patterns from raw conversations.
     */
    USER_PREFERENCE = "USER_PREFERENCE",
    /**
     * Episodic memory strategy - captures meaningful slices of user and system interactions
     */
    EPISODIC = "EPISODIC",
    /**
     * Customize memory processing through custom foundation model and prompt templates.
     */
    CUSTOM = "CUSTOM"
}
/******************************************************************************
 *                                 Common
 *****************************************************************************/
/**
 * Configuration parameters common for any memory strategy
 */
export interface MemoryStrategyCommonProps {
    /**
     * The name for the strategy
     */
    readonly strategyName: string;
    /**
     * The description of the strategy
     * @default - No description
     */
    readonly description?: string;
}
/******************************************************************************
 *                                 Interface
 *****************************************************************************/
/**
 * Interface for Memory strategies
 */
export interface IMemoryStrategy {
    /**
     * The name of the memory strategy
     */
    readonly strategyName: string;
    /**
     * The description of the memory strategy
     */
    readonly description?: string;
    /**
     * The type of memory strategy
     */
    readonly strategyType: MemoryStrategyType;
    /**
     * Renders internal attributes to CloudFormation
     */
    render(): bedrockagentcore.CfnMemory.MemoryStrategyProperty;
    /**
     * Grants the necessary permissions to the role
     * @param grantee - The grantee to grant permissions to
     * @returns The Grant object for chaining
     */
    grant(grantee: iam.IGrantable): iam.Grant | undefined;
}
/******************************************************************************
 *                                 Factory
 *****************************************************************************/
/**
 * 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.
 *
 * @see https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/memory-strategies.html
 */
export declare class MemoryStrategy {
    /**
     * 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 A ManagedMemoryStrategy.
     */
    static usingBuiltInSummarization(): ManagedMemoryStrategy;
    /**
     * Default strategies for organizing and extracting memory data, each optimized for specific use cases.
     * 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.
     */
    static usingBuiltInSemantic(): ManagedMemoryStrategy;
    /**
     * 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 A ManagedMemoryStrategy.
     */
    static usingBuiltInUserPreference(): ManagedMemoryStrategy;
    /**
     * Default strategies for organizing and extracting memory data, each optimized for specific use cases.
     * 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.
     */
    static usingBuiltInEpisodic(): ManagedMemoryStrategy;
    /**
     * Creates a semantic memory strategy with custom configuration.
     * 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.
     * @param config - The configuration for the semantic memory strategy.
     * @returns A ManagedMemoryStrategy.
     */
    static usingSemantic(config: ManagedStrategyProps): ManagedMemoryStrategy;
    /**
     * 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.
     * @param config - The configuration for the user preference memory strategy.
     * @returns A ManagedMemoryStrategy.
     */
    static usingUserPreference(config: ManagedStrategyProps): ManagedMemoryStrategy;
    /**
     * 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.
     * @param config - The configuration for the summarization memory strategy.
     * @returns A ManagedMemoryStrategy.
     */
    static usingSummarization(config: ManagedStrategyProps): ManagedMemoryStrategy;
    /**
     * Creates an episodic memory strategy with custom configuration.
     * 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.
     * @param config - The configuration for the episodic memory strategy.
     * @returns A ManagedMemoryStrategy.
     */
    static usingEpisodic(config: ManagedStrategyProps): ManagedMemoryStrategy;
    /**
     * Creates a self-managed memory strategy.
     * A self-managed strategy gives you complete control over your memory extraction and consolidation pipelines.
     * @param config - The configuration for the self-managed memory strategy.
     * @returns A SelfManagedMemoryStrategy.
     */
    static usingSelfManaged(config: SelfManagedStrategyProps): SelfManagedMemoryStrategy;
}