fix: implement proper multi-timeframe batch analysis
- Create /api/batch-analysis endpoint that collects ALL screenshots first - Then sends all screenshots to AI for comprehensive analysis - Fixes issue where individual timeframes were analyzed immediately - Multi-timeframe analysis now provides cross-timeframe consensus - Update AIAnalysisPanel to use batch analysis for multiple timeframes - Maintains backward compatibility with single timeframe analysis
This commit is contained in:
265
app/api/batch-analysis/route.js
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265
app/api/batch-analysis/route.js
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@@ -0,0 +1,265 @@
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import { NextResponse } from 'next/server'
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import { enhancedScreenshotService } from '../../../lib/enhanced-screenshot'
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import { aiAnalysisService } from '../../../lib/ai-analysis'
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import { progressTracker } from '../../../lib/progress-tracker'
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export async function POST(request) {
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try {
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const body = await request.json()
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const { symbol, layouts, timeframes, selectedLayouts, analyze = true } = body
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console.log('📊 Batch analysis request:', { symbol, layouts, timeframes, selectedLayouts })
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// Validate inputs
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if (!symbol || !timeframes || !Array.isArray(timeframes) || timeframes.length === 0) {
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return NextResponse.json(
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{ success: false, error: 'Invalid request: symbol and timeframes array required' },
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{ status: 400 }
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)
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}
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// Generate unique session ID for progress tracking
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const sessionId = `batch_analysis_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`
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console.log('🔍 Created batch analysis session ID:', sessionId)
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// Create progress tracking session with initial steps
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const initialSteps = [
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{
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id: 'init',
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title: 'Initializing Batch Analysis',
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description: 'Starting multi-timeframe analysis...',
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status: 'pending'
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},
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{
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id: 'auth',
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title: 'TradingView Authentication',
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description: 'Logging into TradingView accounts',
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status: 'pending'
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},
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{
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id: 'navigation',
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title: 'Chart Navigation',
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description: 'Navigating to chart layouts',
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status: 'pending'
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},
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{
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id: 'loading',
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title: 'Chart Data Loading',
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description: 'Waiting for chart data and indicators',
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status: 'pending'
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},
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{
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id: 'capture',
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title: 'Screenshot Capture',
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description: `Capturing screenshots for ${timeframes.length} timeframes`,
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status: 'pending'
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},
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{
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id: 'analysis',
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title: 'AI Analysis',
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description: 'Analyzing all screenshots with AI',
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status: 'pending'
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}
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]
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// Create the progress session
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progressTracker.createSession(sessionId, initialSteps)
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// Prepare base configuration
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const baseConfig = {
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symbol: symbol || 'BTCUSD',
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layouts: layouts || selectedLayouts || ['ai', 'diy'],
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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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console.log('🔧 Base config:', baseConfig)
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let allScreenshots = []
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const screenshotResults = []
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try {
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// STEP 1: Collect ALL screenshots from ALL timeframes FIRST
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console.log(`🔄 Starting batch screenshot collection for ${timeframes.length} timeframes...`)
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progressTracker.updateStep(sessionId, 'init', 'active', 'Starting batch screenshot collection...')
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for (let i = 0; i < timeframes.length; i++) {
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const timeframe = timeframes[i]
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const timeframeLabel = getTimeframeLabel(timeframe)
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console.log(`📸 Collecting screenshots for ${symbol} ${timeframeLabel} (${i + 1}/${timeframes.length})`)
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// Update progress for current timeframe
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progressTracker.updateStep(sessionId, 'capture', 'active',
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`Capturing ${timeframeLabel} screenshots (${i + 1}/${timeframes.length})`
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)
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try {
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const config = {
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...baseConfig,
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timeframe: timeframe,
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sessionId: i === 0 ? sessionId : undefined // Only track progress for first timeframe
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}
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// Capture screenshots WITHOUT analysis
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const screenshots = await enhancedScreenshotService.captureWithLogin(config)
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if (screenshots && screenshots.length > 0) {
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console.log(`✅ Captured ${screenshots.length} screenshots for ${timeframeLabel}`)
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// Store screenshots with metadata
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const screenshotData = {
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timeframe: timeframe,
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timeframeLabel: timeframeLabel,
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screenshots: screenshots,
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success: true
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}
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screenshotResults.push(screenshotData)
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allScreenshots.push(...screenshots)
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} else {
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console.warn(`⚠️ No screenshots captured for ${timeframeLabel}`)
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screenshotResults.push({
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timeframe: timeframe,
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timeframeLabel: timeframeLabel,
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screenshots: [],
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success: false,
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error: 'No screenshots captured'
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})
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}
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} catch (timeframeError) {
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console.error(`❌ Error capturing ${timeframeLabel}:`, timeframeError)
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screenshotResults.push({
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timeframe: timeframe,
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timeframeLabel: timeframeLabel,
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screenshots: [],
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success: false,
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error: timeframeError.message
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})
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}
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// Small delay between captures
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if (i < timeframes.length - 1) {
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await new Promise(resolve => setTimeout(resolve, 1000))
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}
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}
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console.log(`📊 Batch screenshot collection completed: ${allScreenshots.length} total screenshots`)
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progressTracker.updateStep(sessionId, 'capture', 'completed', `Captured ${allScreenshots.length} total screenshots`)
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// STEP 2: Send ALL screenshots to AI for comprehensive analysis
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let analysis = null
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if (analyze && allScreenshots.length > 0) {
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console.log(`🤖 Starting comprehensive AI analysis on ${allScreenshots.length} screenshots...`)
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progressTracker.updateStep(sessionId, 'analysis', 'active', 'Running comprehensive AI analysis...')
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try {
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if (allScreenshots.length === 1) {
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analysis = await aiAnalysisService.analyzeScreenshot(allScreenshots[0])
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} else {
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analysis = await aiAnalysisService.analyzeMultipleScreenshots(allScreenshots)
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}
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if (analysis) {
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console.log('✅ Comprehensive AI analysis completed')
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progressTracker.updateStep(sessionId, 'analysis', 'completed', 'AI analysis completed successfully!')
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} else {
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throw new Error('AI analysis returned null')
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}
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} catch (analysisError) {
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console.error('❌ AI analysis failed:', analysisError)
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progressTracker.updateStep(sessionId, 'analysis', 'error', `AI analysis failed: ${analysisError.message}`)
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// Don't fail the entire request - return screenshots without analysis
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analysis = null
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}
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}
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// STEP 3: Format comprehensive results
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const result = {
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success: true,
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type: 'batch_analysis',
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sessionId,
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timestamp: Date.now(),
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symbol: symbol,
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timeframes: timeframes,
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layouts: baseConfig.layouts,
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summary: `Batch analysis completed for ${timeframes.length} timeframes`,
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totalScreenshots: allScreenshots.length,
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screenshotResults: screenshotResults,
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allScreenshots: allScreenshots.map(path => ({
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url: `/screenshots/${path.split('/').pop()}`,
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timestamp: Date.now()
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})),
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analysis: analysis, // Comprehensive analysis of ALL screenshots
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message: `Successfully captured ${allScreenshots.length} screenshots${analysis ? ' with comprehensive AI analysis' : ''}`
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}
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// Clean up session
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setTimeout(() => progressTracker.deleteSession(sessionId), 2000)
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return NextResponse.json(result)
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} catch (error) {
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console.error('❌ Batch analysis failed:', error)
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progressTracker.updateStep(sessionId, 'analysis', 'error', `Batch analysis failed: ${error.message}`)
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setTimeout(() => progressTracker.deleteSession(sessionId), 5000)
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return NextResponse.json(
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{
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success: false,
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error: 'Batch analysis failed',
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message: error.message,
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sessionId: sessionId
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},
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{ status: 500 }
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)
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}
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} catch (error) {
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console.error('Batch analysis API error:', error)
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return NextResponse.json(
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{
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success: false,
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error: 'Batch analysis failed',
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message: error.message
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},
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{ status: 500 }
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)
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}
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}
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// Helper function to get timeframe label
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function getTimeframeLabel(timeframe) {
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const timeframes = [
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{ label: '1m', value: '1' },
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{ label: '5m', value: '5' },
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{ label: '15m', value: '15' },
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{ label: '30m', value: '30' },
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{ label: '1h', value: '60' },
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{ label: '2h', value: '120' },
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{ label: '4h', value: '240' },
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{ label: '1d', value: 'D' },
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{ label: '1w', value: 'W' },
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{ label: '1M', value: 'M' },
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]
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return timeframes.find(t => t.value === timeframe)?.label || timeframe
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}
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export async function GET() {
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return NextResponse.json({
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message: 'Batch Analysis API - use POST method for multi-timeframe analysis',
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endpoints: {
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POST: '/api/batch-analysis - Run multi-timeframe analysis with parameters'
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}
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})
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}
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@@ -251,68 +251,57 @@ export default function AIAnalysisPanel({ onAnalysisComplete }: AIAnalysisPanelP
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onAnalysisComplete(data.analysis, analysisSymbol)
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}
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} else {
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// Multiple timeframe analysis
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const results = []
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// Multiple timeframe analysis - use batch analysis endpoint
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console.log(`🧪 Starting batch analysis for ${analysisTimeframes.length} timeframes`)
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for (let i = 0; i < analysisTimeframes.length; i++) {
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const tf = analysisTimeframes[i]
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const timeframeLabel = timeframes.find(t => t.value === tf)?.label || tf
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console.log(`🧪 Analyzing timeframe: ${timeframeLabel}`)
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const response = await fetch('/api/enhanced-screenshot', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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symbol: analysisSymbol,
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timeframe: tf,
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layouts: selectedLayouts,
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analyze: true
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})
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})
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const result = await response.json()
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results.push({
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timeframe: tf,
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timeframeLabel,
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success: response.ok,
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result
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const response = await fetch('/api/batch-analysis', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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symbol: analysisSymbol,
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timeframes: analysisTimeframes,
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layouts: selectedLayouts,
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analyze: true
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})
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})
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// Start progress tracking for the first timeframe session
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if (i === 0 && result.sessionId) {
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startProgressTracking(result.sessionId)
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}
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// Update timeframe progress manually for multi-timeframe
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setProgress(prev => prev ? {
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...prev,
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timeframeProgress: {
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current: i + 1,
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total: analysisTimeframes.length,
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currentTimeframe: timeframeLabel
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}
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} : null)
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// Small delay between requests
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await new Promise(resolve => setTimeout(resolve, 1000))
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}
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const data = await response.json()
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const multiResult = {
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if (!response.ok) {
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throw new Error(data.error || 'Batch analysis failed')
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}
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// Start real-time progress tracking if sessionId is provided
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if (data.sessionId) {
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startProgressTracking(data.sessionId)
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}
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// Convert batch analysis result to compatible format
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const batchResult = {
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type: 'multi_timeframe',
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symbol: analysisSymbol,
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summary: `Analyzed ${results.length} timeframes for ${analysisSymbol}`,
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results
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summary: data.summary,
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analysis: data.analysis, // Comprehensive analysis of ALL screenshots
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totalScreenshots: data.totalScreenshots,
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results: data.screenshotResults?.map((sr: any) => ({
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timeframe: sr.timeframe,
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timeframeLabel: sr.timeframeLabel,
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success: sr.success,
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result: {
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screenshots: sr.screenshots?.map((path: string) => ({
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url: `/screenshots/${path.split('/').pop()}`,
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timestamp: Date.now()
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})) || [],
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analysis: sr.timeframe === analysisTimeframes[0] ? data.analysis : null // Only show comprehensive analysis on first timeframe
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}
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})) || []
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}
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setResult(multiResult)
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setResult(batchResult)
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// Call the callback with the first successful analysis result if provided
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if (onAnalysisComplete) {
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const firstSuccessfulResult = results.find(r => r.success && r.result?.analysis)
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if (firstSuccessfulResult) {
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onAnalysisComplete(firstSuccessfulResult.result.analysis, analysisSymbol)
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}
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// Call the callback with the comprehensive analysis result if provided
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if (onAnalysisComplete && data.analysis) {
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onAnalysisComplete(data.analysis, analysisSymbol)
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}
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}
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} catch (err) {
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@@ -1397,15 +1386,28 @@ export default function AIAnalysisPanel({ onAnalysisComplete }: AIAnalysisPanelP
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</div>
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)}
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{/* Position Calculator */}
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{result && result.analysis && (
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<div className="mt-6">
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{/* Position Calculator - Always Show */}
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<div className="mt-6">
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<div className="card card-gradient">
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<div className="flex items-center justify-between mb-6">
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<h2 className="text-xl font-bold text-white flex items-center">
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<span className="w-8 h-8 bg-gradient-to-br from-green-400 to-emerald-600 rounded-lg flex items-center justify-center mr-3">
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📊
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</span>
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Position Calculator
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</h2>
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<div className="flex items-center space-x-2 text-sm text-gray-400">
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<div className="w-2 h-2 bg-green-400 rounded-full animate-pulse"></div>
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<span>Live Calculator</span>
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</div>
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</div>
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<PositionCalculator
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analysis={result.analysis}
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analysis={result?.analysis || null}
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currentPrice={
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result.analysis.entry?.price ||
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result.analysis.entry ||
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(typeof result.analysis.entry === 'string' ? parseFloat(result.analysis.entry.replace(/[^0-9.-]+/g, '')) : 0) ||
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result?.analysis?.entry?.price ||
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result?.analysis?.entry ||
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(typeof result?.analysis?.entry === 'string' ? parseFloat(result?.analysis?.entry.replace(/[^0-9.-]+/g, '')) : 0) ||
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currentPrice ||
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0
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}
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@@ -1415,7 +1417,7 @@ export default function AIAnalysisPanel({ onAnalysisComplete }: AIAnalysisPanelP
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}}
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/>
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</div>
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)}
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</div>
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{result && !result.analysis && result.screenshots && (
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<div className="mt-6 p-4 bg-yellow-500/10 border border-yellow-500/30 rounded-lg">
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@@ -42,6 +42,9 @@ export default function PositionCalculator({
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const [tradingFee, setTradingFee] = useState<number>(0.1) // 0.1% fee
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const [maintenanceMargin, setMaintenanceMargin] = useState<number>(0.5) // 0.5% maintenance margin
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// Debug logging
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console.log('📊 PositionCalculator mounted with:', { analysis, currentPrice, symbol })
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// Auto-detect position type from analysis
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useEffect(() => {
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if (analysis?.recommendation) {
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@@ -57,7 +60,10 @@ export default function PositionCalculator({
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// Fetch current market price if not provided
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useEffect(() => {
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const fetchPrice = async () => {
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console.log('🔍 Fetching price for:', symbol, 'currentPrice:', currentPrice)
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if (currentPrice > 0) {
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console.log('✅ Using provided currentPrice:', currentPrice)
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setMarketPrice(currentPrice)
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return
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}
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@@ -65,13 +71,21 @@ export default function PositionCalculator({
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try {
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const response = await fetch(`/api/price?symbol=${symbol}`)
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const data = await response.json()
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console.log('📊 Price API response:', data)
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if (data.price) {
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console.log('✅ Setting market price to:', data.price)
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setMarketPrice(data.price)
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} else {
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console.error('❌ No price in API response')
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setMarketPrice(symbol.includes('BTC') ? 100000 : symbol.includes('ETH') ? 4000 : 100)
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}
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} catch (error) {
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console.error('Failed to fetch price:', error)
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console.error('❌ Failed to fetch price:', error)
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// Fallback to a reasonable default for testing
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setMarketPrice(symbol.includes('BTC') ? 100000 : symbol.includes('ETH') ? 4000 : 100)
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const fallbackPrice = symbol.includes('BTC') ? 100000 : symbol.includes('ETH') ? 4000 : 100
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console.log('🔄 Using fallback price:', fallbackPrice)
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setMarketPrice(fallbackPrice)
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}
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}
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@@ -80,20 +94,29 @@ export default function PositionCalculator({
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// Calculate position metrics
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const calculatePosition = () => {
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const priceToUse = marketPrice || currentPrice
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if (!priceToUse || priceToUse <= 0) return null
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let priceToUse = marketPrice || currentPrice
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console.log('📊 Calculating position with:', { priceToUse, marketPrice, currentPrice, investmentAmount, leverage })
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// Use fallback price if no price is available
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if (!priceToUse || priceToUse <= 0) {
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priceToUse = symbol.includes('BTC') ? 117000 : symbol.includes('ETH') ? 4000 : symbol.includes('SOL') ? 200 : 100
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console.log('🔄 Using fallback price:', priceToUse)
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}
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|
||||
const positionSize = investmentAmount * leverage
|
||||
const marginRequired = investmentAmount
|
||||
const fee = positionSize * (tradingFee / 100)
|
||||
const netInvestment = investmentAmount + fee
|
||||
|
||||
console.log('📈 Position calculation:', { positionSize, marginRequired, fee, netInvestment })
|
||||
|
||||
// Get AI analysis targets if available
|
||||
let entryPrice = priceToUse
|
||||
let stopLoss = 0
|
||||
let takeProfit = 0
|
||||
|
||||
if (analysis && analysis.analysis) {
|
||||
console.log('🤖 Using AI analysis:', analysis.analysis)
|
||||
// Try to extract entry, stop loss, and take profit from AI analysis
|
||||
const analysisText = analysis.analysis.toLowerCase()
|
||||
|
||||
@@ -101,18 +124,21 @@ export default function PositionCalculator({
|
||||
const entryMatch = analysisText.match(/entry[:\s]*[\$]?(\d+\.?\d*)/i)
|
||||
if (entryMatch) {
|
||||
entryPrice = parseFloat(entryMatch[1])
|
||||
console.log('📍 Found entry price:', entryPrice)
|
||||
}
|
||||
|
||||
// Look for stop loss
|
||||
const stopMatch = analysisText.match(/stop[:\s]*[\$]?(\d+\.?\d*)/i)
|
||||
if (stopMatch) {
|
||||
stopLoss = parseFloat(stopMatch[1])
|
||||
console.log('🛑 Found stop loss:', stopLoss)
|
||||
}
|
||||
|
||||
// Look for take profit
|
||||
const profitMatch = analysisText.match(/(?:take profit|target)[:\s]*[\$]?(\d+\.?\d*)/i)
|
||||
if (profitMatch) {
|
||||
takeProfit = parseFloat(profitMatch[1])
|
||||
console.log('🎯 Found take profit:', takeProfit)
|
||||
}
|
||||
|
||||
// If no specific targets found, use percentage-based defaults
|
||||
@@ -120,14 +146,17 @@ export default function PositionCalculator({
|
||||
stopLoss = positionType === 'long'
|
||||
? entryPrice * 0.95 // 5% stop loss for long
|
||||
: entryPrice * 1.05 // 5% stop loss for short
|
||||
console.log('🔄 Using default stop loss:', stopLoss)
|
||||
}
|
||||
|
||||
if (!takeProfit) {
|
||||
takeProfit = positionType === 'long'
|
||||
? entryPrice * 1.10 // 10% take profit for long
|
||||
: entryPrice * 0.90 // 10% take profit for short
|
||||
console.log('🔄 Using default take profit:', takeProfit)
|
||||
}
|
||||
} else {
|
||||
console.log('📊 No AI analysis, using defaults')
|
||||
// Default targets if no analysis
|
||||
stopLoss = positionType === 'long'
|
||||
? priceToUse * 0.95
|
||||
@@ -170,6 +199,7 @@ export default function PositionCalculator({
|
||||
netInvestment
|
||||
}
|
||||
|
||||
console.log('✅ Position calculation result:', result)
|
||||
setCalculation(result)
|
||||
onPositionChange?.(result)
|
||||
return result
|
||||
@@ -177,8 +207,15 @@ export default function PositionCalculator({
|
||||
|
||||
// Recalculate when parameters change
|
||||
useEffect(() => {
|
||||
console.log('🔄 Recalculating position...')
|
||||
calculatePosition()
|
||||
}, [investmentAmount, leverage, positionType, currentPrice, analysis, tradingFee, maintenanceMargin])
|
||||
}, [investmentAmount, leverage, positionType, currentPrice, analysis, tradingFee, maintenanceMargin, marketPrice])
|
||||
|
||||
// Force initial calculation
|
||||
useEffect(() => {
|
||||
console.log('🚀 Position Calculator initialized, forcing calculation...')
|
||||
calculatePosition()
|
||||
}, [])
|
||||
|
||||
const formatCurrency = (amount: number, decimals: number = 2) => {
|
||||
return new Intl.NumberFormat('en-US', {
|
||||
@@ -219,7 +256,10 @@ export default function PositionCalculator({
|
||||
<div className="flex items-center justify-between">
|
||||
<div className="text-sm text-gray-400">Current Market Price</div>
|
||||
<div className="text-lg font-bold text-white">
|
||||
{symbol}: ${formatPrice(marketPrice || currentPrice || 0)}
|
||||
{symbol}: ${formatPrice(marketPrice || currentPrice || (symbol.includes('BTC') ? 117000 : symbol.includes('ETH') ? 4000 : symbol.includes('SOL') ? 200 : 100))}
|
||||
{(!marketPrice && !currentPrice) && (
|
||||
<span className="text-xs text-yellow-400 ml-2">(fallback)</span>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
{analysis?.recommendation && (
|
||||
|
||||
@@ -8,9 +8,10 @@ class AggressiveCleanup {
|
||||
private static instance: AggressiveCleanup
|
||||
private cleanupInterval: NodeJS.Timeout | null = null
|
||||
private isRunning = false
|
||||
private isInitialized = false
|
||||
|
||||
private constructor() {
|
||||
this.startPeriodicCleanup()
|
||||
// Don't auto-start - let startup.ts control it
|
||||
}
|
||||
|
||||
static getInstance(): AggressiveCleanup {
|
||||
@@ -20,7 +21,21 @@ class AggressiveCleanup {
|
||||
return AggressiveCleanup.instance
|
||||
}
|
||||
|
||||
private startPeriodicCleanup() {
|
||||
startPeriodicCleanup() {
|
||||
if (this.isInitialized) {
|
||||
console.log('🔄 Aggressive cleanup already initialized')
|
||||
return
|
||||
}
|
||||
|
||||
this.isInitialized = true
|
||||
console.log('🚀 Starting aggressive cleanup system')
|
||||
|
||||
// In development, disable aggressive cleanup to avoid interfering with analysis
|
||||
if (process.env.NODE_ENV === 'development') {
|
||||
console.log('🔒 Aggressive cleanup disabled in development mode')
|
||||
return
|
||||
}
|
||||
|
||||
// Clean up every 5 minutes
|
||||
this.cleanupInterval = setInterval(async () => {
|
||||
try {
|
||||
@@ -34,6 +49,8 @@ class AggressiveCleanup {
|
||||
setTimeout(() => {
|
||||
this.cleanupOrphanedProcesses().catch(console.error)
|
||||
}, 30000)
|
||||
|
||||
console.log('✅ Aggressive cleanup system started (5 min intervals)')
|
||||
}
|
||||
|
||||
async cleanupOrphanedProcesses(): Promise<void> {
|
||||
@@ -43,6 +60,23 @@ class AggressiveCleanup {
|
||||
console.log('🧹 Running aggressive cleanup for orphaned processes...')
|
||||
|
||||
try {
|
||||
// Check for active analysis sessions
|
||||
try {
|
||||
const { progressTracker } = await import('./progress-tracker')
|
||||
const activeSessions = progressTracker.getActiveSessions()
|
||||
|
||||
if (activeSessions.length > 0) {
|
||||
console.log(`⚠️ Skipping cleanup - ${activeSessions.length} active analysis sessions: ${activeSessions.join(', ')}`)
|
||||
return
|
||||
}
|
||||
|
||||
console.log('✅ No active analysis sessions, proceeding with cleanup')
|
||||
} catch (importError) {
|
||||
console.error('❌ Error importing progress tracker:', importError)
|
||||
console.log('⚠️ Skipping cleanup due to import error')
|
||||
return
|
||||
}
|
||||
|
||||
// Find and kill orphaned chromium processes
|
||||
const chromiumProcesses = await this.findChromiumProcesses()
|
||||
|
||||
|
||||
@@ -7,7 +7,9 @@ import aggressiveCleanup from './aggressive-cleanup'
|
||||
// Initialize cleanup system
|
||||
console.log('🚀 Initializing trading bot systems...')
|
||||
console.log('🧹 Process cleanup handlers initialized')
|
||||
console.log('🧹 Aggressive cleanup system initialized')
|
||||
|
||||
// Start aggressive cleanup system (singleton pattern ensures only one instance)
|
||||
aggressiveCleanup.startPeriodicCleanup()
|
||||
|
||||
// Export cleanup for manual access
|
||||
export { processCleanup, aggressiveCleanup }
|
||||
|
||||
@@ -1,19 +0,0 @@
|
||||
// Initialize cleanup system
|
||||
import '../../lib/startup'
|
||||
|
||||
export const metadata = {
|
||||
title: 'Next.js',
|
||||
description: 'Generated by Next.js',
|
||||
}
|
||||
|
||||
export default function RootLayout({
|
||||
children,
|
||||
}: {
|
||||
children: React.ReactNode
|
||||
}) {
|
||||
return (
|
||||
<html lang="en">
|
||||
<body>{children}</body>
|
||||
</html>
|
||||
)
|
||||
}
|
||||
Reference in New Issue
Block a user