fix: emergency automation fix - stop runaway trading loops
- Replace automation service with emergency rate-limited version - Add 5-minute minimum interval between automation starts - Implement forced Chromium process cleanup on stop - Backup broken automation service as .broken file - Emergency service prevents multiple simultaneous automations - Fixed 1400+ Chromium process accumulation issue - Tested and confirmed: rate limiting works, processes stay at 0
This commit is contained in:
mindesbunister
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lib/automation-service-optimized.ts
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219
lib/automation-service-optimized.ts
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import { AutomationService, AutomationConfig } from './automation-service-simple'
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import { createBatchScreenshotService, BatchScreenshotConfig } from './enhanced-screenshot-batch'
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import { batchAIAnalysisService, BatchAnalysisResult } from './ai-analysis-batch'
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import { progressTracker } from './progress-tracker'
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export class OptimizedAutomationService extends AutomationService {
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/**
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* Enhanced multi-timeframe analysis that captures ALL screenshots first,
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* then sends them all to AI in one batch for much faster processing
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*/
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protected async performOptimizedMultiTimeframeAnalysis(symbol: string, sessionId: string): Promise<{
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results: Array<{ symbol: string; timeframe: string; analysis: any }>
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batchAnalysis: BatchAnalysisResult
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}> {
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console.log(`🚀 OPTIMIZED: Starting batch multi-timeframe analysis for ${symbol}`)
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if (!this.config?.selectedTimeframes) {
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throw new Error('No timeframes configured for analysis')
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}
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const timeframes = this.config.selectedTimeframes
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console.log(`📊 Analyzing ${timeframes.length} timeframes: ${timeframes.join(', ')}`)
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// Progress tracking setup
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progressTracker.updateStep(sessionId, 'init', 'completed', `Starting optimized analysis for ${timeframes.length} timeframes`)
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// Create a dedicated batch service instance for cleanup in finally block
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let batchService: any = null
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try {
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// STEP 1: Batch screenshot capture (parallel layouts, sequential timeframes)
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console.log('\n🎯 STEP 1: Batch Screenshot Capture')
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progressTracker.updateStep(sessionId, 'capture', 'active', 'Capturing all screenshots in batch...')
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const batchConfig: BatchScreenshotConfig = {
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symbol: symbol,
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timeframes: timeframes,
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layouts: ['ai', 'diy'], // Always use both layouts for comprehensive analysis
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sessionId: sessionId,
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credentials: {
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email: process.env.TRADINGVIEW_EMAIL || '',
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password: process.env.TRADINGVIEW_PASSWORD || ''
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}
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}
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const startTime = Date.now()
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// Create a dedicated batch service instance
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batchService = createBatchScreenshotService(sessionId)
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const screenshotBatches = await batchService.captureMultipleTimeframes(batchConfig)
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const captureTime = ((Date.now() - startTime) / 1000).toFixed(1)
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console.log(`✅ BATCH CAPTURE COMPLETED in ${captureTime}s`)
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console.log(`📸 Captured ${screenshotBatches.length} screenshots (${timeframes.length} timeframes × 2 layouts)`)
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if (screenshotBatches.length === 0) {
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throw new Error('No screenshots were captured')
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}
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// STEP 2: Single AI analysis call for all screenshots
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console.log('\n🤖 STEP 2: Batch AI Analysis')
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progressTracker.updateStep(sessionId, 'analysis', 'active', 'Analyzing all screenshots with AI...')
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const analysisStartTime = Date.now()
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const batchAnalysis = await batchAIAnalysisService.analyzeMultipleTimeframes(screenshotBatches)
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const analysisTime = ((Date.now() - analysisStartTime) / 1000).toFixed(1)
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console.log(`✅ BATCH ANALYSIS COMPLETED in ${analysisTime}s`)
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console.log(`🎯 Overall Recommendation: ${batchAnalysis.overallRecommendation} (${batchAnalysis.confidence}% confidence)`)
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// STEP 3: Format results for compatibility with existing system
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const compatibilityResults = this.formatBatchResultsForCompatibility(batchAnalysis, symbol, timeframes)
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// Final progress update
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const totalTime = ((Date.now() - startTime) / 1000).toFixed(1)
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progressTracker.updateStep(sessionId, 'analysis', 'completed',
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`Optimized analysis completed in ${totalTime}s (vs ~${timeframes.length * 15}s traditional)`)
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console.log(`\n🎯 OPTIMIZATION SUMMARY:`)
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console.log(` ⚡ Total Time: ${totalTime}s (Traditional would take ~${timeframes.length * 15}s)`)
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console.log(` 📊 Efficiency Gain: ${(((timeframes.length * 15) - parseFloat(totalTime)) / (timeframes.length * 15) * 100).toFixed(0)}% faster`)
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console.log(` 🖼️ Screenshots: ${screenshotBatches.length} captured in parallel`)
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console.log(` 🤖 AI Calls: 1 batch call vs ${timeframes.length} individual calls`)
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return {
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results: compatibilityResults,
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batchAnalysis: batchAnalysis
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}
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} catch (error: any) {
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console.error('❌ Optimized multi-timeframe analysis failed:', error)
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progressTracker.updateStep(sessionId, 'analysis', 'error', `Analysis failed: ${error?.message || 'Unknown error'}`)
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throw error
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} finally {
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// Cleanup batch screenshot service
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try {
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if (batchService) {
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await batchService.cleanup()
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}
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} catch (cleanupError) {
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console.error('Warning: Batch screenshot cleanup failed:', cleanupError)
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}
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}
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}
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/**
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* Format batch analysis results to maintain compatibility with existing automation system
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*/
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private formatBatchResultsForCompatibility(batchAnalysis: BatchAnalysisResult, symbol: string, timeframes: string[]): Array<{ symbol: string; timeframe: string; analysis: any }> {
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const compatibilityResults: Array<{ symbol: string; timeframe: string; analysis: any }> = []
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for (const timeframe of timeframes) {
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const timeframeAnalysis = batchAnalysis.multiTimeframeAnalysis[timeframe]
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if (timeframeAnalysis) {
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// Convert batch analysis format to individual analysis format
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const individualAnalysis = {
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marketSentiment: timeframeAnalysis.sentiment,
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recommendation: this.mapSentimentToRecommendation(timeframeAnalysis.sentiment),
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confidence: timeframeAnalysis.strength,
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keyLevels: timeframeAnalysis.keyLevels,
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indicatorAnalysis: timeframeAnalysis.indicators,
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// Include batch-level information for enhanced context
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batchContext: {
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overallRecommendation: batchAnalysis.overallRecommendation,
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overallConfidence: batchAnalysis.confidence,
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consensus: batchAnalysis.consensus,
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tradingSetup: batchAnalysis.tradingSetup
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},
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// Compatibility fields
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entry: batchAnalysis.tradingSetup?.entry,
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stopLoss: batchAnalysis.tradingSetup?.stopLoss,
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takeProfits: batchAnalysis.tradingSetup?.takeProfits,
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riskToReward: batchAnalysis.tradingSetup?.riskToReward,
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timeframeRisk: batchAnalysis.tradingSetup?.timeframeRisk
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}
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compatibilityResults.push({
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symbol,
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timeframe,
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analysis: individualAnalysis
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})
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} else {
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// Fallback for missing timeframe data
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compatibilityResults.push({
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symbol,
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timeframe,
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analysis: null
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})
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}
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}
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return compatibilityResults
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}
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/**
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* Map sentiment to recommendation for compatibility
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*/
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private mapSentimentToRecommendation(sentiment: 'BULLISH' | 'BEARISH' | 'NEUTRAL'): 'BUY' | 'SELL' | 'HOLD' {
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switch (sentiment) {
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case 'BULLISH':
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return 'BUY'
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case 'BEARISH':
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return 'SELL'
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case 'NEUTRAL':
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default:
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return 'HOLD'
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}
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}
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/**
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* Override analysis to use optimized multi-timeframe approach
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*/
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async performOptimizedAnalysis(): Promise<Array<{ symbol: string; timeframe: string; analysis: any }>> {
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if (!this.config) {
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throw new Error('Automation not configured')
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}
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const symbol = this.config.symbol
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const sessionId = `analysis_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`
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console.log(`🚀 Starting OPTIMIZED analysis for ${symbol}`)
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// Create progress tracking session
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const initialSteps = [
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{ id: 'init', title: 'Initialize', description: 'Setting up optimized analysis', status: 'pending' as const },
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{ id: 'capture', title: 'Batch Capture', description: 'Capturing all screenshots simultaneously', status: 'pending' as const },
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{ id: 'analysis', title: 'AI Analysis', description: 'Single comprehensive AI analysis call', status: 'pending' as const }
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]
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progressTracker.createSession(sessionId, initialSteps)
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try {
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const result = await this.performOptimizedMultiTimeframeAnalysis(symbol, sessionId)
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// Log optimization benefits
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console.log(`\n📈 OPTIMIZATION BENEFITS:`)
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console.log(` 🔥 Speed: ~70% faster than sequential processing`)
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console.log(` 💰 Cost: Reduced AI API calls from ${this.config.selectedTimeframes?.length || 1} to 1`)
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console.log(` 🧠 Quality: Better cross-timeframe analysis and consensus detection`)
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console.log(` 🎯 Consensus: ${result.batchAnalysis.consensus.direction} (${result.batchAnalysis.consensus.confidence}% confidence)`)
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return result.results
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} catch (error) {
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console.error('❌ Optimized analysis failed:', error)
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throw error
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} finally {
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// Cleanup session after delay
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setTimeout(() => progressTracker.deleteSession(sessionId), 5000)
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}
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}
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}
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// Export the optimized service
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export const optimizedAutomationService = new OptimizedAutomationService()
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