Eliza🎓 高级主题信任引擎

🤝 信任引擎

概述

信任引擎是一个复杂的系统，用于评估、跟踪和管理代币推荐和交易活动的信任分数。它结合了链上分析、交易者指标和历史表现，创建了一个全面的信任框架。

核心组件

信任分数数据库

数据库模式管理信任的各个方面：

interface TrustScoreDatabase {
  // 核心数据结构
  recommenders: Recommender[]
  metrics: RecommenderMetrics[]
  tokenPerformance: TokenPerformance[]
  recommendations: TokenRecommendation[]
}
 
interface Recommender {
  id: string
  address: string
  solanaPubkey?: string
  telegramId?: string
  discordId?: string
  twitterId?: string
  ip?: string
}
 
interface RecommenderMetrics {
  recommenderId: string
  trustScore: number
  totalRecommendations: number
  successfulRecs: number
  avgTokenPerformance: number
  riskScore: number
  consistencyScore: number
  virtualConfidence: number
  lastActiveDate: Date
}

代币分析

系统跟踪全面的代币指标：

interface TokenPerformance {
  tokenAddress: string
  priceChange24h: number
  volumeChange24h: number
  trade_24h_change: number
  liquidity: number
  liquidityChange24h: number
  holderChange24h: number
  rugPull: boolean
  isScam: boolean
  marketCapChange24h: number
  sustainedGrowth: boolean
  rapidDump: boolean
  suspiciousVolume: boolean
  validationTrust: number
  lastUpdated: Date
}

信任评分系统

分数计算

async function calculateTrustScore(recommenderId: string, metrics: RecommenderMetrics): Promise<number> {
  const weights = {
    successRate: 0.3,
    avgPerformance: 0.2,
    consistency: 0.2,
    riskMetric: 0.15,
    timeDecay: 0.15,
  }
 
  const successRate = metrics.successfulRecs / metrics.totalRecommendations
  const normalizedPerformance = normalizePerformance(metrics.avgTokenPerformance)
  const timeDecayFactor = calculateTimeDecay(metrics.lastActiveDate)
 
  return (
    (successRate * weights.successRate +
      normalizedPerformance * weights.avgPerformance +
      metrics.consistencyScore * weights.consistency +
      (1 - metrics.riskScore) * weights.riskMetric +
      timeDecayFactor * weights.timeDecay) *
    100
  )
}

代币验证

async function validateToken(tokenAddress: string, performance: TokenPerformance): Promise<boolean> {
  // 最低要求
  const requirements = {
    minLiquidity: 1000, // 1000 美元
    minHolders: 100,
    maxOwnership: 0.2, // 单个持有者最大 20%
    minVolume: 500, // 每日 500 美元的交易量
  }
 
  // 危险信号
  if (performance.rugPull || performance.isScam || performance.rapidDump || performance.suspiciousVolume) {
    return false
  }
 
  // 基本要求
  return (
    performance.liquidity >= requirements.minLiquidity && !performance.rapidDump && performance.validationTrust > 0.5
  )
}

交易管理

交易表现跟踪

interface TradePerformance {
  token_address: string
  recommender_id: string
  buy_price: number
  sell_price: number
  buy_timeStamp: string
  sell_timeStamp: string
  profit_usd: number
  profit_percent: number
  market_cap_change: number
  liquidity_change: number
  rapidDump: boolean
}
 
async function recordTradePerformance(trade: TradePerformance, isSimulation: boolean): Promise<void> {
  const tableName = isSimulation ? 'simulation_trade' : 'trade'
  await db.query(
    `
        INSERT INTO ${tableName} (
            token_address,
            recommender_id,
            buy_price,
            sell_price,
            buy_timeStamp,
            sell_timeStamp,
            profit_usd,
            profit_percent,
            market_cap_change,
            liquidity_change,
            rapidDump
        ) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11)
    `,
    [
      /* 参数 */
    ],
  )
}

风险管理

async function assessTradeRisk(
  token: TokenPerformance,
  recommender: RecommenderMetrics,
): Promise<{
  riskLevel: 'LOW' | 'MEDIUM' | 'HIGH'
  maxPositionSize: number
}> {
  const riskFactors = {
    tokenTrust: token.validationTrust,
    recommenderTrust: recommender.trustScore,
    marketMetrics: {
      liquidity: token.liquidity,
      volume: token.volumeChange24h,
      holders: token.holderChange24h,
    },
  }
 
  // 计算综合风险分数
  const riskScore = calculateRiskScore(riskFactors)
 
  // 确定头寸规模
  const maxPosition = determinePositionSize(riskScore)
 
  return {
    riskLevel: getRiskLevel(riskScore),
    maxPositionSize: maxPosition,
  }
}

推荐分析

模式检测

async function analyzeRecommendationPatterns(recommenderId: string): Promise<RecommendationPattern> {
  const history = await getRecommenderHistory(recommenderId)
 
  return {
    timeOfDay: analyzeTimingPatterns(history),
    tokenTypes: analyzeTokenPreferences(history),
    successRateByType: calculateTypeSuccessRates(history),
    riskProfile: assessRiskProfile(history),
  }
}

性能指标

interface PerformanceMetrics {
  profitability: number
  consistency: number
  riskAdjustedReturn: number
  maxDrawdown: number
  winRate: number
}
 
async function calculatePerformanceMetrics(recommendations: TokenRecommendation[]): Promise<PerformanceMetrics> {
  const trades = await getTradesFromRecommendations(recommendations)
 
  return {
    profitability: calculateProfitability(trades),
    consistency: calculateConsistency(trades),
    riskAdjustedReturn: calculateSharpeRatio(trades),
    maxDrawdown: calculateMaxDrawdown(trades),
    winRate: calculateWinRate(trades),
  }
}

与交易系统集成

交易执行

async function executeTrade(recommendation: TokenRecommendation, trustScore: number): Promise<boolean> {
  const riskAssessment = await assessTradeRisk(recommendation.tokenAddress, recommendation.recommenderId)
 
  // 根据信任分数计算头寸规模
  const positionSize = calculatePositionSize(trustScore, riskAssessment.maxPositionSize)
 
  if (positionSize > 0) {
    await executeSwap({
      inputToken: 'SOL',
      outputToken: recommendation.tokenAddress,
      amount: positionSize,
    })
 
    await recordTradeEntry(recommendation, positionSize)
    return true
  }
 
  return false
}

头寸管理

async function managePosition(position: TradePosition, metrics: TokenPerformance): Promise<void> {
  // 退出条件
  if (metrics.rapidDump || metrics.suspiciousVolume || calculateDrawdown(position) > MAX_DRAWDOWN) {
    await executeExit(position)
    return
  }
 
  // 头寸规模调整
  const newSize = recalculatePosition(position, metrics)
  if (newSize !== position.size) {
    await adjustPosition(position, newSize)
  }
}

监控和警报

性能监控

async function monitorTrustMetrics(): Promise<void> {
  // 监控信任分数变化
  const scoreChanges = await getTrustScoreChanges()
  for (const change of scoreChanges) {
    if (Math.abs(change.delta) > TRUST_THRESHOLD) {
      await notifyTrustChange(change)
    }
  }
 
  // 监控交易表现
  const performanceMetrics = await getPerformanceMetrics()
  for (const metric of performanceMetrics) {
    if (metric.drawdown > MAX_DRAWDOWN) {
      await notifyRiskAlert(metric)
    }
  }
}

警报系统

interface TrustAlert {
  type: 'SCORE_CHANGE' | 'RISK_LEVEL' | 'PERFORMANCE'
  severity: 'LOW' | 'MEDIUM' | 'HIGH'
  message: string
  data: any
}
 
async function handleAlert(alert: TrustAlert): Promise<void> {
  switch (alert.severity) {
    case 'HIGH':
      await sendImmediateNotification(alert)
      await pauseTrading(alert.data)
      break
    case 'MEDIUM':
      await sendNotification(alert)
      await adjustRiskLevels(alert.data)
      break
    case 'LOW':
      await logAlert(alert)
      break
  }
}

故障排除

常见问题

  1. 信任分数异常
async function investigateTrustAnomaly(recommenderId: string): Promise<AnomalyReport> {
  const history = await getRecommenderHistory(recommenderId)
  const metrics = await getRecommenderMetrics(recommenderId)
  const trades = await getRecommenderTrades(recommenderId)
 
  return analyzeAnomalies(history, metrics, trades)
}
  1. 交易执行失败
async function handleTradeFailure(error: Error, trade: TradeAttempt): Promise<void> {
  await logTradeError(error, trade)
  await adjustTrustScore(trade.recommenderId, 'FAILURE')
  await notifyTradeFailure(trade)
}
基础设施自主交易