claude-flow
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Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
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TypeScript
/**
* Balanced Mode Implementation
*
* General-purpose mode with:
* - +25% quality improvement
* - 18ms overhead
* - Rank-4 LoRA
* - Pattern caching
* - Standard learning pipeline
*/
import type { SONAModeConfig, Trajectory, Pattern, PatternMatch, LoRAWeights, EWCState } from '../types.js';
import { BaseModeImplementation } from './index.js';
/**
* Balanced mode for general-purpose learning
*/
export declare class BalancedMode extends BaseModeImplementation {
readonly mode = "balanced";
private patternCache;
private cacheHits;
private cacheMisses;
private gradientAccumulator;
private momentumBuffers;
private totalPatternMatches;
private totalPatternTime;
private totalLearnTime;
private learnIterations;
private qualityImprovements;
initialize(): Promise<void>;
cleanup(): Promise<void>;
/**
* Find patterns using similarity search with caching
*/
findPatterns(embedding: Float32Array, k: number, patterns: Pattern[]): Promise<PatternMatch[]>;
/**
* Learn from trajectories using standard gradient descent
*/
learn(trajectories: Trajectory[], config: SONAModeConfig, ewcState: EWCState): Promise<number>;
/**
* Apply LoRA adaptations with rank-4
*/
applyLoRA(input: Float32Array, weights?: LoRAWeights): Promise<Float32Array>;
getStats(): Record<string, number>;
/**
* Compute cache key from embedding
*/
private computeCacheKey;
/**
* Compute gradient from state and reward
*/
private computeGradient;
/**
* Accumulate gradient with momentum
*/
private accumulateGradient;
/**
* Compute EWC penalty for continual learning
*/
private computeEWCPenalty;
}
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