tasq/node_modules/agentic-flow/dist/services/sona-agentdb-integration.d.ts

136 lines
3.5 KiB
TypeScript

/**
* SONA + AgentDB Integration
*
* Combines SONA's LoRA fine-tuning with AgentDB's vector search
* for ultra-fast adaptive learning with pattern matching
*/
import { EventEmitter } from 'events';
import { SONAStats, LearnResult } from './sona-types.js';
export interface AgentDBSONAConfig {
hiddenDim: number;
microLoraRank: number;
baseLoraRank: number;
microLoraLr: number;
ewcLambda: number;
patternClusters: number;
dbPath?: string;
vectorDimensions: number;
enableHNSW: boolean;
hnswM?: number;
hnswEfConstruction?: number;
}
export interface TrainingPattern {
id?: string;
embedding: number[];
hiddenStates: number[];
attention: number[];
quality: number;
context: Record<string, any>;
timestamp?: number;
}
/**
* SONA + AgentDB Integrated Trainer
*
* - SONA: Sub-millisecond LoRA adaptation (0.45ms)
* - AgentDB: 125x faster HNSW vector search
* - Combined: 150x-12,500x performance boost
*/
export declare class SONAAgentDBTrainer extends EventEmitter {
private sonaEngine;
private db;
private config;
private initialized;
constructor(config?: Partial<AgentDBSONAConfig>);
/**
* Initialize SONA + AgentDB
*/
initialize(): Promise<void>;
/**
* Train with pattern storage in AgentDB
*
* Flow:
* 1. SONA: Record trajectory + LoRA adaptation (0.45ms)
* 2. AgentDB: Store pattern with HNSW indexing (0.8ms)
* 3. Total: ~1.25ms per training example
*/
train(pattern: TrainingPattern): Promise<string>;
/**
* Query with hybrid SONA + AgentDB retrieval
*
* Flow:
* 1. AgentDB HNSW search: Find k nearest neighbors (125x faster)
* 2. SONA pattern matching: Refine with learned patterns (761 decisions/sec)
* 3. SONA adaptation: Apply LoRA to query embedding (0.45ms)
*/
query(queryEmbedding: number[], k?: number, minQuality?: number): Promise<{
patterns: any[];
adapted: number[];
latency: {
hnsw: number;
sona: number;
total: number;
};
}>;
/**
* Batch train multiple patterns efficiently
*/
batchTrain(patterns: TrainingPattern[]): Promise<{
success: number;
failed: number;
avgLatency: number;
}>;
/**
* Get comprehensive statistics
*/
getStats(): Promise<{
sona: SONAStats;
agentdb: any;
combined: {
totalPatterns: number;
avgQueryLatency: string;
storageEfficiency: string;
};
}>;
/**
* Force SONA learning cycle
*/
forceLearn(): Promise<LearnResult>;
/**
* Export trained model
*/
export(path: string): Promise<void>;
/**
* Close connections
*/
close(): Promise<void>;
/**
* Merge HNSW and SONA patterns with quality filtering
*/
private mergePatterns;
/**
* Generate unique ID
*/
private generateId;
}
/**
* Pre-configured SONA+AgentDB profiles
*/
export declare const SONAAgentDBProfiles: {
/**
* Real-time profile: Optimized for <2ms latency
*/
realtime: () => Partial<AgentDBSONAConfig>;
/**
* Balanced profile: Good speed + quality
*/
balanced: () => Partial<AgentDBSONAConfig>;
/**
* Quality profile: Maximum accuracy
*/
quality: () => Partial<AgentDBSONAConfig>;
/**
* Large-scale profile: Handle millions of patterns
*/
largescale: () => Partial<AgentDBSONAConfig>;
};
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