- Fixed field mapping between API and frontend (amount→positionSize, entry→entryPrice, createdAt→timestamp) - Updated API sync function to properly convert API trade format to frontend format - Resolved display issues: 'Invalid Date', missing entry price, missing trade size - Added trade monitoring system and automation improvements - Enhanced automation with simple-automation.js for reliable 24/7 operation - Working automation now detecting 85% confidence BUY signals and executing trades
117 lines
3.4 KiB
JavaScript
117 lines
3.4 KiB
JavaScript
import { NextResponse } from 'next/server'
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// Simple in-memory storage for paper trades (in production, use database)
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let paperTrades = []
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let tradeIdCounter = 1
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// Export function to get trades (for other API routes)
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export function getAllPaperTrades() {
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return paperTrades
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}
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export async function POST(request) {
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try {
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const tradeData = await request.json()
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// Validate required fields
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const required = ['symbol', 'side', 'amount', 'entry', 'confidence']
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for (const field of required) {
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if (!tradeData[field]) {
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return NextResponse.json({
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success: false,
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message: `Missing required field: ${field}`
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}, { status: 400 })
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}
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}
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// Create paper trade
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const trade = {
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id: `PAPER_${Date.now()}_${tradeIdCounter++}`,
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symbol: tradeData.symbol,
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side: tradeData.side,
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amount: tradeData.amount,
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entry: tradeData.entry,
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stopLoss: tradeData.stopLoss,
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takeProfit: tradeData.takeProfit,
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confidence: tradeData.confidence,
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reasoning: tradeData.reasoning,
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source: tradeData.source || 'manual',
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status: 'OPEN',
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createdAt: new Date().toISOString(),
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pnl: 0,
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fees: 0
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}
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// Store trade
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paperTrades.push(trade)
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console.log(`📄 Paper trade created: ${trade.id} - ${trade.side} ${trade.symbol} at $${trade.entry} (${trade.confidence}% confidence)`)
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// Log to AI learning system if available
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try {
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const learningData = {
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id: `decision_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`,
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symbol: trade.symbol,
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timeframe: '60',
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side: trade.side,
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confidence: trade.confidence,
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entry: trade.entry,
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stopLoss: trade.stopLoss,
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takeProfit: trade.takeProfit,
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reasoning: trade.reasoning,
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source: 'paper_trade_automation',
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createdAt: new Date().toISOString()
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}
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// Store in learning system (try to call learning API)
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fetch('http://localhost:9001/api/ai-learning/record-decision', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(learningData)
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}).catch(error => {
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console.log('⚠️ Could not log to learning system:', error.message)
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})
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} catch (error) {
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console.log('⚠️ Learning system integration error:', error.message)
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}
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return NextResponse.json({
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success: true,
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message: 'Paper trade created successfully',
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trade: trade
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})
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} catch (error) {
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console.error('❌ Create paper trade error:', error)
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return NextResponse.json({
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success: false,
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message: 'Failed to create paper trade',
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error: error.message
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}, { status: 500 })
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}
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}
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export async function GET(request) {
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try {
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// Return all paper trades
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return NextResponse.json({
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success: true,
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trades: paperTrades,
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summary: {
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total: paperTrades.length,
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open: paperTrades.filter(t => t.status === 'OPEN').length,
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closed: paperTrades.filter(t => t.status === 'CLOSED').length,
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totalPnL: paperTrades.reduce((sum, t) => sum + (t.pnl || 0), 0)
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}
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})
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} catch (error) {
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console.error('❌ Get paper trades error:', error)
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return NextResponse.json({
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success: false,
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message: 'Failed to get paper trades',
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error: error.message
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}, { status: 500 })
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}
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}
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