Spaces:
Paused
Paused
File size: 6,637 Bytes
529090e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 | import { neo4jService } from '../../database/Neo4jService';
/**
* Self-Reflection Engine
* Enables agents to assess their own performance and improve
*/
export interface PerformanceMetrics {
taskId: string;
agentId: string;
success: boolean;
duration: number;
errorType?: string;
timestamp: Date;
context: Record<string, any>;
}
export interface ReflectionInsight {
pattern: string;
frequency: number;
impact: 'positive' | 'negative' | 'neutral';
recommendation: string;
confidence: number;
}
export class SelfReflectionEngine {
private performanceLog: PerformanceMetrics[] = [];
private insights: ReflectionInsight[] = [];
/**
* Log performance data
*/
logPerformance(metrics: PerformanceMetrics): void {
this.performanceLog.push(metrics);
// Keep only last 1000 entries
if (this.performanceLog.length > 1000) {
this.performanceLog.shift();
}
}
/**
* Analyze error patterns
*/
analyzeErrorPatterns(agentId?: string): Map<string, number> {
const errors = this.performanceLog.filter(log =>
!log.success && (!agentId || log.agentId === agentId)
);
const errorCounts = new Map<string, number>();
errors.forEach(error => {
if (error.errorType) {
errorCounts.set(error.errorType, (errorCounts.get(error.errorType) || 0) + 1);
}
});
return errorCounts;
}
/**
* Evaluate strategy effectiveness
*/
evaluateStrategyEffectiveness(
strategy: string,
timeWindow: number = 7 * 24 * 60 * 60 * 1000 // 7 days
): {
successRate: number;
avgDuration: number;
totalAttempts: number;
} {
const cutoff = new Date(Date.now() - timeWindow);
const relevant = this.performanceLog.filter(log =>
log.timestamp > cutoff &&
log.context.strategy === strategy
);
if (relevant.length === 0) {
return { successRate: 0, avgDuration: 0, totalAttempts: 0 };
}
const successes = relevant.filter(log => log.success).length;
const totalDuration = relevant.reduce((sum, log) => sum + log.duration, 0);
return {
successRate: successes / relevant.length,
avgDuration: totalDuration / relevant.length,
totalAttempts: relevant.length,
};
}
/**
* Generate improvement recommendations
*/
async generateRecommendations(agentId: string): Promise<ReflectionInsight[]> {
const errorPatterns = this.analyzeErrorPatterns(agentId);
const recommendations: ReflectionInsight[] = [];
// Analyze error patterns
errorPatterns.forEach((count, errorType) => {
if (count > 5) {
recommendations.push({
pattern: `Frequent ${errorType} errors`,
frequency: count,
impact: 'negative',
recommendation: `Implement better error handling for ${errorType}`,
confidence: Math.min(count / 10, 1),
});
}
});
// Analyze performance trends
const recentPerformance = this.performanceLog
.filter(log => log.agentId === agentId)
.slice(-50);
if (recentPerformance.length > 10) {
const successRate = recentPerformance.filter(log => log.success).length / recentPerformance.length;
if (successRate < 0.7) {
recommendations.push({
pattern: 'Low success rate',
frequency: recentPerformance.length,
impact: 'negative',
recommendation: 'Review task assignment criteria and agent capabilities',
confidence: 1 - successRate,
});
} else if (successRate > 0.95) {
recommendations.push({
pattern: 'High success rate',
frequency: recentPerformance.length,
impact: 'positive',
recommendation: 'Consider taking on more complex tasks',
confidence: successRate,
});
}
}
this.insights = recommendations;
return recommendations;
}
/**
* Continuous improvement loop
*/
async runImprovementCycle(agentId: string): Promise<void> {
const recommendations = await this.generateRecommendations(agentId);
// Store insights in Neo4j for long-term learning
try {
await neo4jService.connect();
for (const insight of recommendations) {
await neo4jService.runQuery(
`MERGE (a:Agent {id: $agentId})
CREATE (i:Insight {
pattern: $pattern,
recommendation: $recommendation,
confidence: $confidence,
timestamp: datetime()
})
CREATE (a)-[:HAS_INSIGHT]->(i)`,
{
agentId,
pattern: insight.pattern,
recommendation: insight.recommendation,
confidence: insight.confidence,
}
);
}
await neo4jService.disconnect();
} catch (error) {
console.error('Failed to store insights:', error);
}
console.log(`🔍 Generated ${recommendations.length} improvement recommendations for ${agentId}`);
}
/**
* Get performance summary
*/
getPerformanceSummary(agentId: string, days: number = 7): {
totalTasks: number;
successRate: number;
avgDuration: number;
errorBreakdown: Map<string, number>;
} {
const cutoff = new Date(Date.now() - days * 24 * 60 * 60 * 1000);
const relevant = this.performanceLog.filter(log =>
log.agentId === agentId && log.timestamp > cutoff
);
const successes = relevant.filter(log => log.success).length;
const totalDuration = relevant.reduce((sum, log) => sum + log.duration, 0);
return {
totalTasks: relevant.length,
successRate: relevant.length > 0 ? successes / relevant.length : 0,
avgDuration: relevant.length > 0 ? totalDuration / relevant.length : 0,
errorBreakdown: this.analyzeErrorPatterns(agentId),
};
}
}
export const selfReflectionEngine = new SelfReflectionEngine();
|