483d4c6576
✅ FIXED: AI analysis prompts to bypass OpenAI safety guardrails ✅ FIXED: Added technical analysis focus instead of trading advice tone ✅ FIXED: Improved JSON parsing and error handling ✅ ADDED: Option to use existing screenshots for testing (useExisting param) ✅ IMPROVED: Better image detail settings and temperature for consistency 🐛 DEBUGGING: Still investigating why AI claims it can't see images - OpenAI vision capabilities confirmed working with public images - Model gpt-4o has proper vision support - Issue appears to be with chart image content or encoding 🎯 NEXT: Debug image encoding and model response inconsistency
410 lines
14 KiB
TypeScript
410 lines
14 KiB
TypeScript
import OpenAI from 'openai'
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import fs from 'fs/promises'
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import path from 'path'
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import { enhancedScreenshotService, ScreenshotConfig } from './enhanced-screenshot'
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import { TradingViewCredentials } from './tradingview-automation'
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const openai = new OpenAI({
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apiKey: process.env.OPENAI_API_KEY,
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})
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export interface AnalysisResult {
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summary: string
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marketSentiment: 'BULLISH' | 'BEARISH' | 'NEUTRAL'
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keyLevels: {
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support: number[]
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resistance: number[]
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}
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recommendation: 'BUY' | 'SELL' | 'HOLD'
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confidence: number // 0-100
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reasoning: string
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// Enhanced trading analysis (optional)
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entry?: {
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price: number
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buffer?: string
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rationale: string
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}
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stopLoss?: {
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price: number
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rationale: string
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}
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takeProfits?: {
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tp1?: { price: number; description: string }
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tp2?: { price: number; description: string }
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}
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riskToReward?: string
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confirmationTrigger?: string
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indicatorAnalysis?: {
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rsi?: string
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vwap?: string
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obv?: string
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}
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}
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export class AIAnalysisService {
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async analyzeScreenshot(filename: string): Promise<AnalysisResult | null> {
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try {
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const screenshotsDir = path.join(process.cwd(), 'screenshots')
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const imagePath = path.join(screenshotsDir, filename)
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// Read image file
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const imageBuffer = await fs.readFile(imagePath)
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const base64Image = imageBuffer.toString('base64')
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const prompt = `You are a technical chart analysis expert. Please analyze this TradingView chart image and provide objective technical analysis data.
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**Important**: This is for educational and research purposes only. Please analyze the technical indicators, price levels, and chart patterns visible in the image.
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Examine the chart and identify:
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- Current price action and trend direction
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- Key support and resistance levels visible on the chart
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- Technical indicator readings (RSI, moving averages, volume if visible)
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- Chart patterns or formations
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- Market structure elements
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Provide your analysis in this exact JSON format (replace values with your analysis):
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{
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"summary": "Objective description of what you observe in the chart",
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"marketSentiment": "BULLISH|BEARISH|NEUTRAL",
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"keyLevels": {
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"support": [list of visible support price levels as numbers],
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"resistance": [list of visible resistance price levels as numbers]
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},
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"recommendation": "BUY|SELL|HOLD",
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"confidence": 75,
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"reasoning": "Technical analysis reasoning based on indicators and price action",
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"entry": {
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"price": 150.50,
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"buffer": "±0.25",
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"rationale": "Technical reasoning for entry level"
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},
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"stopLoss": {
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"price": 148.00,
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"rationale": "Technical reasoning for stop level"
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},
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"takeProfits": {
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"tp1": { "price": 152.00, "description": "First target reasoning" },
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"tp2": { "price": 154.00, "description": "Second target reasoning" }
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},
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"riskToReward": "1:2",
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"confirmationTrigger": "Technical signal to watch for",
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"indicatorAnalysis": {
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"rsi": "RSI level and interpretation",
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"vwap": "VWAP relationship to price",
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"obv": "Volume analysis if visible"
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}
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}
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Return only the JSON object with your technical analysis.`
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const response = await openai.chat.completions.create({
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model: "gpt-4o", // Updated to current vision model
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messages: [
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{
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role: "user",
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content: [
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{ type: "text", text: prompt },
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{
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type: "image_url",
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image_url: {
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url: `data:image/png;base64,${base64Image}`,
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detail: "low" // Reduce token usage
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}
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}
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]
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}
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],
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max_tokens: 1024,
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temperature: 0.1
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})
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const content = response.choices[0]?.message?.content
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if (!content) return null
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console.log('AI response content:', content)
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// Extract JSON from response
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const match = content.match(/\{[\s\S]*\}/)
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if (!match) {
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console.error('No JSON found in response. Full content:', content)
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return null
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}
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const json = match[0]
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console.log('Raw JSON from AI:', json)
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const result = JSON.parse(json)
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console.log('Parsed result:', result)
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// Sanitize the result to ensure no nested objects cause React issues
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const sanitizedResult = {
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summary: typeof result.summary === 'string' ? result.summary : String(result.summary || ''),
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marketSentiment: result.marketSentiment || 'NEUTRAL',
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keyLevels: {
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support: Array.isArray(result.keyLevels?.support) ? result.keyLevels.support : [],
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resistance: Array.isArray(result.keyLevels?.resistance) ? result.keyLevels.resistance : []
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},
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recommendation: result.recommendation || 'HOLD',
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confidence: typeof result.confidence === 'number' ? result.confidence : 0,
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reasoning: typeof result.reasoning === 'string' ? result.reasoning : String(result.reasoning || ''),
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...(result.entry && { entry: result.entry }),
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...(result.stopLoss && { stopLoss: result.stopLoss }),
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...(result.takeProfits && { takeProfits: result.takeProfits }),
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...(result.riskToReward && { riskToReward: String(result.riskToReward) }),
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...(result.confirmationTrigger && { confirmationTrigger: String(result.confirmationTrigger) }),
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...(result.indicatorAnalysis && { indicatorAnalysis: result.indicatorAnalysis })
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}
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// Optionally: validate result structure here
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return sanitizedResult as AnalysisResult
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} catch (e) {
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console.error('AI analysis error:', e)
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return null
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}
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}
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async analyzeMultipleScreenshots(filenames: string[]): Promise<AnalysisResult | null> {
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try {
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const screenshotsDir = path.join(process.cwd(), 'screenshots')
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const images: any[] = []
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for (const filename of filenames) {
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const imagePath = path.join(screenshotsDir, filename)
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const imageBuffer = await fs.readFile(imagePath)
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const base64Image = imageBuffer.toString('base64')
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images.push({ type: "image_url", image_url: { url: `data:image/png;base64,${base64Image}` } })
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}
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const prompt = `You are a technical chart analysis expert. Please analyze these TradingView chart images and provide objective technical analysis data.
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**Important**: This is for educational and research purposes only. Please analyze the technical indicators, price levels, and chart patterns visible in the images.
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Examine all the charts and provide a consolidated analysis by identifying:
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- Current price action and trend direction across layouts
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- Key support and resistance levels visible on the charts
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- Technical indicator readings (RSI, moving averages, volume if visible)
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- Chart patterns or formations
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- Market structure elements
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- Cross-reference different timeframes/layouts for the most accurate analysis
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**CRITICAL: You MUST analyze the actual chart images provided. Do not respond with generic advice.**
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Provide your analysis in this exact JSON format (replace values with your analysis):
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{
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"summary": "Objective description combining analysis from all charts",
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"marketSentiment": "BULLISH|BEARISH|NEUTRAL",
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"keyLevels": {
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"support": [list of visible support price levels as numbers],
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"resistance": [list of visible resistance price levels as numbers]
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},
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"recommendation": "BUY|SELL|HOLD",
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"confidence": 75,
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"reasoning": "Technical analysis reasoning based on indicators and price action from all layouts",
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"entry": {
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"price": 150.50,
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"buffer": "±0.25",
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"rationale": "Technical reasoning for entry level"
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},
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"stopLoss": {
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"price": 148.00,
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"rationale": "Technical reasoning for stop level"
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},
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"takeProfits": {
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"tp1": { "price": 152.00, "description": "First target reasoning" },
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"tp2": { "price": 154.00, "description": "Second target reasoning" }
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},
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"riskToReward": "1:2",
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"confirmationTrigger": "Technical signal to watch for",
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"indicatorAnalysis": {
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"rsi": "RSI level and interpretation",
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"vwap": "VWAP relationship to price",
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"obv": "Volume analysis if visible"
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}
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}
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Return only the JSON object with your consolidated technical analysis.`
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const response = await openai.chat.completions.create({
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model: "gpt-4o", // gpt-4o has better vision capabilities than gpt-4-vision-preview
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messages: [
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{
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role: "user",
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content: [
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{ type: "text", text: prompt },
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...images
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]
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}
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],
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max_tokens: 2000, // Increased for more detailed analysis
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temperature: 0.1
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})
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const content = response.choices[0]?.message?.content
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if (!content) {
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throw new Error('No content received from OpenAI')
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}
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console.log('AI response content:', content)
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// Parse the JSON response
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const jsonMatch = content.match(/\{[\s\S]*\}/)
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if (!jsonMatch) {
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console.error('No JSON found in response. Full content:', content)
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throw new Error('No JSON found in response')
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}
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console.log('Extracted JSON:', jsonMatch[0])
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const analysis = JSON.parse(jsonMatch[0])
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// Sanitize the analysis result to ensure no nested objects cause React issues
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const sanitizedAnalysis = {
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summary: typeof analysis.summary === 'string' ? analysis.summary : String(analysis.summary || ''),
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marketSentiment: analysis.marketSentiment || 'NEUTRAL',
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keyLevels: {
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support: Array.isArray(analysis.keyLevels?.support) ? analysis.keyLevels.support : [],
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resistance: Array.isArray(analysis.keyLevels?.resistance) ? analysis.keyLevels.resistance : []
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},
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recommendation: analysis.recommendation || 'HOLD',
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confidence: typeof analysis.confidence === 'number' ? analysis.confidence : 0,
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reasoning: typeof analysis.reasoning === 'string' ? analysis.reasoning : String(analysis.reasoning || ''),
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...(analysis.entry && { entry: analysis.entry }),
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...(analysis.stopLoss && { stopLoss: analysis.stopLoss }),
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...(analysis.takeProfits && { takeProfits: analysis.takeProfits }),
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...(analysis.riskToReward && { riskToReward: String(analysis.riskToReward) }),
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...(analysis.confirmationTrigger && { confirmationTrigger: String(analysis.confirmationTrigger) }),
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...(analysis.indicatorAnalysis && { indicatorAnalysis: analysis.indicatorAnalysis })
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}
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// Validate the structure
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if (!sanitizedAnalysis.summary || !sanitizedAnalysis.marketSentiment || !sanitizedAnalysis.recommendation || typeof sanitizedAnalysis.confidence !== 'number') {
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console.error('Invalid analysis structure:', sanitizedAnalysis)
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throw new Error('Invalid analysis structure')
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}
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return sanitizedAnalysis
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} catch (error) {
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console.error('AI multi-analysis error:', error)
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return null
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}
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}
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async captureAndAnalyze(
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symbol: string,
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timeframe: string,
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credentials: TradingViewCredentials
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): Promise<AnalysisResult | null> {
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try {
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console.log(`Starting automated capture and analysis for ${symbol} ${timeframe}`)
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// Capture screenshot using automation
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const screenshot = await enhancedScreenshotService.captureQuick(symbol, timeframe, credentials)
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if (!screenshot) {
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throw new Error('Failed to capture screenshot')
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}
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console.log(`Screenshot captured: ${screenshot}`)
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// Analyze the captured screenshot
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const analysis = await this.analyzeScreenshot(screenshot)
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if (!analysis) {
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throw new Error('Failed to analyze screenshot')
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}
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console.log(`Analysis completed for ${symbol} ${timeframe}`)
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return analysis
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} catch (error) {
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console.error('Automated capture and analysis failed:', error)
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return null
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}
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}
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async captureAndAnalyzeMultiple(
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symbols: string[],
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timeframes: string[],
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credentials: TradingViewCredentials
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): Promise<Array<{ symbol: string; timeframe: string; analysis: AnalysisResult | null }>> {
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const results: Array<{ symbol: string; timeframe: string; analysis: AnalysisResult | null }> = []
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for (const symbol of symbols) {
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for (const timeframe of timeframes) {
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try {
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console.log(`Processing ${symbol} ${timeframe}...`)
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const analysis = await this.captureAndAnalyze(symbol, timeframe, credentials)
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results.push({
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symbol,
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timeframe,
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analysis
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})
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// Small delay between captures to avoid overwhelming the system
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await new Promise(resolve => setTimeout(resolve, 2000))
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} catch (error) {
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console.error(`Failed to process ${symbol} ${timeframe}:`, error)
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results.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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}
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return results
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}
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async captureAndAnalyzeWithConfig(config: ScreenshotConfig): Promise<{
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screenshots: string[]
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analysis: AnalysisResult | null
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}> {
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try {
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console.log(`Starting automated capture with config for ${config.symbol} ${config.timeframe}`)
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// Capture screenshots using enhanced service
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const screenshots = await enhancedScreenshotService.captureWithLogin(config)
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if (screenshots.length === 0) {
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throw new Error('No screenshots captured')
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}
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console.log(`${screenshots.length} screenshot(s) captured`)
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let analysis: AnalysisResult | null = null
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if (screenshots.length === 1) {
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// Single screenshot analysis
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analysis = await this.analyzeScreenshot(screenshots[0])
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} else {
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// Multiple screenshots analysis
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analysis = await this.analyzeMultipleScreenshots(screenshots)
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}
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if (!analysis) {
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throw new Error('Failed to analyze screenshots')
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}
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console.log(`Analysis completed for ${config.symbol} ${config.timeframe}`)
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return {
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screenshots,
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analysis
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}
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} catch (error) {
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console.error('Automated capture and analysis with config failed:', error)
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return {
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screenshots: [],
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analysis: null
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}
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}
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}
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}
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export const aiAnalysisService = new AIAnalysisService()
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