tasq/node_modules/@claude-flow/neural/dist/sona-manager.d.ts

147 lines
4.2 KiB
TypeScript

/**
* SONA Manager - Self-Optimizing Neural Architecture
*
* Manages learning modes and provides adaptive optimization for agent tasks.
*
* Performance Targets:
* - Adaptation: <0.05ms
* - Pattern retrieval: <1ms
* - Learning step: <10ms
*
* Supported Modes:
* - real-time: Sub-millisecond adaptation (2200 ops/sec)
* - balanced: General purpose (+25% quality)
* - research: Deep exploration (+55% quality)
* - edge: Resource-constrained (<5MB)
* - batch: High-throughput processing
*/
import type { SONAMode, SONAModeConfig, ModeOptimizations, Trajectory, Pattern, PatternMatch, NeuralStats, NeuralEventListener, LoRAConfig, LoRAWeights, EWCConfig } from './types.js';
/**
* SONA Manager - Main orchestrator for neural learning
*/
export declare class SONAManager {
private currentMode;
private config;
private optimizations;
private modeImpl;
private trajectories;
private patterns;
private loraWeights;
private ewcState;
private eventListeners;
private stats;
private isInitialized;
private operationCount;
private totalLatencyMs;
private learningCycles;
private lastStatsUpdate;
constructor(mode?: SONAMode);
/**
* Initialize the SONA manager
*/
initialize(): Promise<void>;
/**
* Change the current learning mode
*/
setMode(mode: SONAMode): Promise<void>;
/**
* Get current mode and configuration
*/
getConfig(): {
mode: SONAMode;
config: SONAModeConfig;
optimizations: ModeOptimizations;
};
/**
* Begin a new trajectory for a task
*/
beginTrajectory(context: string, domain?: Trajectory['domain']): string;
/**
* Record a step in a trajectory
*/
recordStep(trajectoryId: string, action: string, reward: number, stateEmbedding: Float32Array, metadata?: Record<string, unknown>): void;
/**
* Complete a trajectory
*/
completeTrajectory(trajectoryId: string, finalQuality?: number): Trajectory | null;
/**
* Get a trajectory by ID
*/
getTrajectory(trajectoryId: string): Trajectory | undefined;
/**
* Find similar patterns for a given context (k=3 optimal)
*/
findSimilarPatterns(embedding: Float32Array, k?: number): Promise<PatternMatch[]>;
/**
* Store a new pattern
*/
storePattern(pattern: Omit<Pattern, 'patternId' | 'createdAt' | 'updatedAt'>): Pattern;
/**
* Update pattern based on usage
*/
updatePatternUsage(patternId: string, quality: number): void;
/**
* Trigger a learning cycle
*/
triggerLearning(reason?: string): Promise<void>;
/**
* Apply learned adaptations to processing
*/
applyAdaptations(input: Float32Array, domain?: string): Promise<Float32Array>;
/**
* Get LoRA configuration for current mode
*/
getLoRAConfig(): LoRAConfig;
/**
* Initialize LoRA weights for a domain
*/
initializeLoRAWeights(domain?: string): LoRAWeights;
/**
* Get EWC configuration
*/
getEWCConfig(): EWCConfig;
/**
* Consolidate EWC after learning a new task
*/
consolidateEWC(): void;
/**
* Get current neural system statistics
*/
getStats(): NeuralStats;
/**
* Add an event listener
*/
addEventListener(listener: NeuralEventListener): void;
/**
* Remove an event listener
*/
removeEventListener(listener: NeuralEventListener): void;
/**
* Cleanup resources
*/
cleanup(): Promise<void>;
private createModeImplementation;
private calculateQualityScore;
private checkLearningTrigger;
private pruneTrajectories;
private trackLatency;
private emitEvent;
private createInitialStats;
private updateStats;
private estimateMemoryUsage;
private estimateTrajectoryBytes;
private estimatePatternBytes;
}
/**
* Factory function for creating SONA manager
*/
export declare function createSONAManager(mode?: SONAMode): SONAManager;
/**
* Get default configuration for a mode
*/
export declare function getModeConfig(mode: SONAMode): SONAModeConfig;
/**
* Get optimizations for a mode
*/
export declare function getModeOptimizations(mode: SONAMode): ModeOptimizations;
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