import OpenAI from 'openai' import fs from 'fs/promises' import path from 'path' const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY, }) export interface AnalysisResult { summary: string marketSentiment: 'BULLISH' | 'BEARISH' | 'NEUTRAL' keyLevels: { support: number[] resistance: number[] } recommendation: 'BUY' | 'SELL' | 'HOLD' confidence: number // 0-100 reasoning: string } export class AIAnalysisService { async analyzeScreenshot(filename: string): Promise { try { const screenshotsDir = path.join(process.cwd(), 'screenshots') const imagePath = path.join(screenshotsDir, filename) // Read image file const imageBuffer = await fs.readFile(imagePath) const base64Image = imageBuffer.toString('base64') const prompt = `You are now a professional trading assistant focused on short-term crypto trading using 5–15min timeframes. You behave with the precision and decisiveness of a top proprietary desk trader. No vagueness, no fluff. Analyze the attached TradingView chart screenshot and provide a detailed trading analysis. ### WHEN GIVING A TRADE SETUP: Be 100% SPECIFIC. Provide: 1. **ENTRY** - Exact price level (with a ± entry buffer if needed) - Rationale: e.g., "Rejection from 15 EMA + VWAP confluence near intraday supply" 2. **STOP-LOSS (SL)** - Exact level (not arbitrary) - Explain *why* it's there: "Above VWAP + failed breakout zone" 3. **TAKE PROFITS** - TP1: Immediate structure (ex: previous low at $149.20) - TP2: Extended target if momentum continues (e.g., $148.00) - Mention **expected RSI/OBV behavior** at each TP zone 4. **RISK-TO-REWARD** - Show R:R. Ex: "1:2.5 — Risking $X to potentially gain $Y" 5. **CONFIRMATION TRIGGER** - Exact signal to wait for: e.g., "Bearish engulfing candle on rejection from VWAP zone" - OBV: "Must be making lower highs + dropping below 30min average" - RSI: "Should remain under 50 on rejection. Overbought ≥70 = wait" 6. **INDICATOR ANALYSIS** - **RSI**: If RSI crosses above 70 while price is under resistance → *wait* - **VWAP**: If price retakes VWAP with bullish momentum → *consider invalidation* - **OBV**: If OBV starts climbing while price stays flat → *early exit or reconsider bias* Return your answer as a JSON object with the following structure: { "summary": "Brief market summary", "marketSentiment": "BULLISH" | "BEARISH" | "NEUTRAL", "keyLevels": { "support": [number array], "resistance": [number array] }, "recommendation": "BUY" | "SELL" | "HOLD", "confidence": number (0-100), "reasoning": "Detailed reasoning with specific levels, indicators, and confirmation triggers" } Be concise but thorough. Only return valid JSON.` const response = await openai.chat.completions.create({ model: "gpt-4o", // Updated to current vision model messages: [ { role: "user", content: [ { type: "text", text: prompt }, { type: "image_url", image_url: { url: `data:image/png;base64,${base64Image}` } } ] } ], max_tokens: 1024 }) const content = response.choices[0]?.message?.content if (!content) return null // Extract JSON from response const match = content.match(/\{[\s\S]*\}/) if (!match) return null const json = match[0] const result = JSON.parse(json) // Optionally: validate result structure here return result as AnalysisResult } catch (e) { console.error('AI analysis error:', e) return null } } async analyzeMultipleScreenshots(filenames: string[]): Promise { try { const screenshotsDir = path.join(process.cwd(), 'screenshots') const images: any[] = [] for (const filename of filenames) { const imagePath = path.join(screenshotsDir, filename) const imageBuffer = await fs.readFile(imagePath) const base64Image = imageBuffer.toString('base64') images.push({ type: "image_url", image_url: { url: `data:image/png;base64,${base64Image}` } }) } const prompt = `You are now a professional trading assistant focused on short-term crypto trading using 5–15min timeframes. You behave with the precision and decisiveness of a top proprietary desk trader. No vagueness, no fluff. Analyze the attached TradingView chart screenshots (multiple layouts of the same symbol) and provide a comprehensive trading analysis by combining insights from all charts. ### WHEN GIVING A TRADE SETUP: Be 100% SPECIFIC. Provide: 1. **ENTRY** - Exact price level (with a ± entry buffer if needed) - Rationale: e.g., "Rejection from 15 EMA + VWAP confluence near intraday supply" 2. **STOP-LOSS (SL)** - Exact level (not arbitrary) - Explain *why* it's there: "Above VWAP + failed breakout zone" 3. **TAKE PROFITS** - TP1: Immediate structure (ex: previous low at $149.20) - TP2: Extended target if momentum continues (e.g., $148.00) - Mention **expected RSI/OBV behavior** at each TP zone 4. **RISK-TO-REWARD** - Show R:R. Ex: "1:2.5 — Risking $X to potentially gain $Y" 5. **CONFIRMATION TRIGGER** - Exact signal to wait for: e.g., "Bearish engulfing candle on rejection from VWAP zone" - OBV: "Must be making lower highs + dropping below 30min average" - RSI: "Should remain under 50 on rejection. Overbought ≥70 = wait" 6. **INDICATOR ANALYSIS** - **RSI**: If RSI crosses above 70 while price is under resistance → *wait* - **VWAP**: If price retakes VWAP with bullish momentum → *consider invalidation* - **OBV**: If OBV starts climbing while price stays flat → *early exit or reconsider bias* Cross-reference all layouts to provide the most accurate analysis. If layouts show conflicting signals, explain which one takes priority and why. Return your answer as a JSON object with the following structure: { "summary": "Brief market summary combining all layouts", "marketSentiment": "BULLISH" | "BEARISH" | "NEUTRAL", "keyLevels": { "support": [number array], "resistance": [number array] }, "recommendation": "BUY" | "SELL" | "HOLD", "confidence": number (0-100), "reasoning": "Detailed reasoning with specific levels, indicators, and confirmation triggers from all layouts" } Be concise but thorough. Only return valid JSON.` const response = await openai.chat.completions.create({ model: "gpt-4o", messages: [ { role: "user", content: [ { type: "text", text: prompt }, ...images ] } ], max_tokens: 1500, temperature: 0.1 }) const content = response.choices[0]?.message?.content if (!content) { throw new Error('No content received from OpenAI') } console.log('AI response content:', content) // Parse the JSON response const jsonMatch = content.match(/\{[\s\S]*\}/) if (!jsonMatch) { console.error('No JSON found in response. Full content:', content) throw new Error('No JSON found in response') } console.log('Extracted JSON:', jsonMatch[0]) const analysis = JSON.parse(jsonMatch[0]) // Validate the structure if (!analysis.summary || !analysis.marketSentiment || !analysis.recommendation || !analysis.confidence) { console.error('Invalid analysis structure:', analysis) throw new Error('Invalid analysis structure') } return analysis } catch (error) { console.error('AI multi-analysis error:', error) return null } } } export const aiAnalysisService = new AIAnalysisService()