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cleanUrl : `https://www.amazon.com${cleanUrl}`;\n}\n\n// Helper function to parse sales volume into numeric value for sorting\nfunction parseSalesVolume(salesText) {\n if (!salesText) return 0;\n \n const text = salesText.toLowerCase();\n \n // Extract number\n const match = text.match(/(\\d+\\.?\\d*)([km]?)\\+?/i);\n if (!match) return 0;\n \n let value = parseFloat(match[1]);\n const multiplier = match[2];\n \n // Apply multiplier\n if (multiplier === 'k') value *= 1000;\n if (multiplier === 'm') value *= 1000000;\n \n return Math.floor(value);\n}\n\n// Helper function to format sales volume for display\nfunction formatSalesVolume(salesText) {\n if (!salesText) return 'N/A';\n return salesText.replace(/bought in past month/gi, '').trim();\n}\n\n// Calculate product score (for smart ranking)\nfunction calculateProductScore(product, salesNumeric) {\n const rating = product.rating || 0;\n const reviews = product.reviews_count || 0;\n const discount = product.price_strikethrough ? \n ((product.price_strikethrough - product.price) / product.price_strikethrough) : 0;\n \n // Weighted scoring\n const ratingScore = rating * 20; // Max 100\n const reviewScore = Math.min(reviews / 100, 50); // Max 50\n const salesScore = Math.min(salesNumeric / 1000, 30); // Max 30\n const discountScore = discount * 20; // Max 20\n \n // Bonus for badges\n const badgeBonus = (product.is_amazons_choice ? 10 : 0) + \n (product.best_seller ? 10 : 0);\n \n return ratingScore + reviewScore + salesScore + discountScore + badgeBonus;\n}\n\n// Extract all products\nfor (const item of inputData) {\n const results = item.json.results?.[0]?.content?.results?.results;\n if (!results) continue;\n \n // Combine paid and organic products\n const allProducts = [\n ...(results.paid || []),\n ...(results.organic || []),\n ...(results.amazons_choices || [])\n ];\n \n allProducts.forEach(p => {\n // Skip if missing critical data\n if (!p.title || !p.price) return;\n \n const salesVolume = parseSalesVolume(p.sales_volume);\n \n products.push({\n title: p.title,\n price: p.price,\n original_price: p.price_strikethrough || null,\n rating: p.rating || 0,\n reviews: p.reviews_count || 0,\n \n // Sales data\n sales_volume_raw: p.sales_volume || 'N/A',\n sales_volume_display: formatSalesVolume(p.sales_volume),\n sales_volume_numeric: salesVolume,\n \n // Discount calculation\n discount: p.price_strikethrough ? \n Math.round(((p.price_strikethrough - p.price) / p.price_strikethrough) * 100) : 0,\n savings: p.price_strikethrough ? \n (p.price_strikethrough - p.price).toFixed(2) : 0,\n \n // CLEAN URL - remove UTM parameters and extract ASIN\n url: cleanAmazonURL(p.url?.startsWith('http') ? p.url : `https://www.amazon.com${p.url}`),\n \n // Badges\n is_amazons_choice: p.is_amazons_choice || false,\n is_bestseller: p.best_seller || false,\n is_sponsored: p.is_sponsored || false,\n \n // Image\n image: p.url_image || null,\n \n // Manufacturer\n brand: p.manufacturer || 'Generic',\n \n // Shipping\n shipping: p.shipping_information || 'See Amazon',\n \n // Calculated score for ranking (weighted)\n score: calculateProductScore(p, salesVolume)\n });\n });\n}\n\n// Remove duplicates (same ASIN)\nconst uniqueProducts = products.reduce((acc, product) => {\n const exists = acc.find(p => p.title === product.title && p.price === product.price);\n if (!exists) acc.push(product);\n return acc;\n}, []);\n\n// Sort by calculated score (best overall value)\nuniqueProducts.sort((a, b) => b.score - a.score);\n\n// Get query\nconst query = $('Extract Chat & Query').first().json.message.replaceAll('+', ' ');\n\n// Calculate statistics\nconst avgPrice = uniqueProducts.reduce((sum, p) => sum + p.price, 0) / uniqueProducts.length;\nconst avgRating = uniqueProducts.reduce((sum, p) => sum + p.rating, 0) / uniqueProducts.length;\nconst totalSales = uniqueProducts.reduce((sum, p) => sum + p.sales_volume_numeric, 0);\n\n// Create AI-ready output with enhanced categorization\nreturn [{\n json: {\n query: query,\n total: uniqueProducts.length,\n \n // Statistics\n stats: {\n avg_price: avgPrice.toFixed(2),\n min_price: Math.min(...uniqueProducts.map(p => p.price)),\n max_price: Math.max(...uniqueProducts.map(p => p.price)),\n avg_rating: avgRating.toFixed(2),\n total_reviews: uniqueProducts.reduce((sum, p) => sum + p.reviews, 0),\n total_sales: totalSales\n },\n \n // Top picks (by overall score)\n top_picks: uniqueProducts.slice(0, 10).map(p => ({\n title: p.title,\n price: p.price,\n rating: p.rating,\n reviews: p.reviews,\n sales: p.sales_volume_display,\n discount: p.discount > 0 ? `${p.discount}% off` : null,\n badges: {\n choice: p.is_amazons_choice,\n bestseller: p.is_bestseller\n },\n url: p.url // Already cleaned by cleanAmazonURL function\n })),\n \n // Budget options (under $30, sorted by rating)\n budget_options: uniqueProducts\n .filter(p => p.price < 30)\n .sort((a, b) => b.rating - a.rating || b.reviews - a.reviews)\n .slice(0, 5)\n .map(p => ({\n title: p.title,\n price: p.price,\n rating: p.rating,\n reviews: p.reviews,\n sales: p.sales_volume_display,\n url: p.url\n })),\n \n // Premium options ($50+, sorted by rating)\n premium_options: uniqueProducts\n .filter(p => p.price >= 50)\n .sort((a, b) => b.rating - a.rating)\n .slice(0, 5)\n .map(p => ({\n title: p.title,\n price: p.price,\n rating: p.rating,\n reviews: p.reviews,\n sales: p.sales_volume_display,\n url: p.url\n })),\n \n // Best rated (4.5+ stars, sorted by reviews)\n best_rated: uniqueProducts\n .filter(p => p.rating >= 4.5)\n .sort((a, b) => b.reviews - a.reviews)\n .slice(0, 5)\n .map(p => ({\n title: p.title,\n price: p.price,\n rating: p.rating,\n reviews: p.reviews,\n sales: p.sales_volume_display,\n url: p.url\n })),\n \n // Best value (highest discount with good rating)\n best_value: uniqueProducts\n .filter(p => p.discount > 0 && p.rating >= 4.0)\n .sort((a, b) => b.discount - a.discount)\n .slice(0, 5)\n .map(p => ({\n title: p.title,\n price: p.price,\n original_price: p.original_price,\n discount: `${p.discount}%`,\n savings: `$${p.savings}`,\n rating: p.rating,\n reviews: p.reviews,\n url: p.url\n })),\n \n // Most popular (by sales volume)\n most_popular: uniqueProducts\n .filter(p => p.sales_volume_numeric > 0)\n .sort((a, b) => b.sales_volume_numeric - a.sales_volume_numeric)\n .slice(0, 5)\n .map(p => ({\n title: p.title,\n price: p.price,\n rating: p.rating,\n sales: p.sales_volume_display,\n sales_count: p.sales_volume_numeric,\n url: p.url\n })),\n \n // Amazon's Choice products\n amazons_choice: uniqueProducts\n .filter(p => p.is_amazons_choice)\n .slice(0, 3)\n .map(p => ({\n title: p.title,\n price: p.price,\n rating: p.rating,\n reviews: p.reviews,\n sales: p.sales_volume_display,\n url: p.url\n })),\n \n // All products (for reference)\n all_products: uniqueProducts\n }\n}];" }, "position": [ 2000, 480 ] }, { "id": "ad548326-555c-41e0-b406-5a6cce340b84", "name": "Generate Recommendations", "type": "llm", "params": { "text": "=You are a product recommendation expert analyzing {{ $json.query }}.\n\nAVAILABLE DATA:\n- Total Products: {{ $json.total }}\n- Price Range: ${{ $json.stats.min_price }} - ${{ $json.stats.max_price }} (avg: ${{ $json.stats.avg_price }})\n- Average Rating: {{ $json.stats.avg_rating }}/5\n- Total Reviews: {{ $json.stats.total_reviews }}\n\nCATEGORIES:\n- Top Picks: {{ $json.top_picks.length }}\n- Budget (<$30): {{ $json.budget_options.length }}\n- Premium ($50+): {{ $json.premium_options.length }}\n- Best Value: {{ $json.best_value.length }}\n- Most Popular: {{ $json.most_popular.length }}\n\nCRITICAL RULES:\n1. MAX 2500 characters\n2. Use TELEGRAM MARKDOWN (legacy):\n - *bold* for headers only\n - No special escaping needed\n - Plain URLs on new lines\n3. SHORTEN product names to max 50 chars\n4. Each product MUST include its Amazon URL\n5. Be DYNAMIC - adapt language to product type\n6. VARIED symbols: 💵📊🔥💰⚡🎒📱🍎✓\n\nOUTPUT FORMAT:\n\n*🏆 TOP 3 PICKS*\n\n*1. [Short Product Name]*\n💵 $[XX] | 📊 [X.X]/5 ([XX]K reviews) | 🔥 [Sales]\n✓ [Key unique feature in 5-8 words]\n✓ [Value reason in 10-15 words]\n🔗 [Full Amazon URL]\n\n*2. [Short Product Name]*\n💵 $[XX] | 📊 [X.X]/5 ([XX]K reviews) | 🔥 [Sales]\n✓ [Key unique feature in 5-8 words]\n✓ [Value reason in 10-15 words]\n🔗 [Full Amazon URL]\n\n*3. [Short Product Name]*\n💵 $[XX] | 📊 [X.X]/5 ([XX]K reviews) | 🔥 [Sales]\n✓ [Key unique feature in 5-8 words]\n✓ [Value reason in 10-15 words]\n🔗 [Full Amazon URL]\n\n━━━━━━━━━━━━━━\n\n*💰 BEST BUDGET*\n[Product Name - shortened]\n💵 $[XX] (was $[Original]) | 📊 [X.X]/5 | 💰 Save $[XX]\nPerfect for: [User type in 8-12 words]\nTrade-off: [What's missing vs premium in 6-10 words]\n🔗 [Full Amazon URL]\n\n*💎 BEST PREMIUM*\n[Product Name - shortened]\n💵 $[XX] | 📊 [X.X]/5 ([XX] reviews)\nWorth it: [Premium features in 12-15 words]\nBest for: [Specific user scenario in 8-10 words]\n🔗 [Full Amazon URL]\n\n━━━━━━━━━━━━━━\n\n*📊 QUICK STATS*\n\n💸 Cheapest: [Name] - $[XX]\n⭐ Top Rated: [Name] - [X.X]/5\n🔥 Most Popular: [Name] - [Sales]\n💰 Best Deal: [Name] - [XX]% off\n\n━━━━━━━━━━━━━━\n\n*🎯 PICK BY NEED*\n\n⚡ [Primary feature need] → [Product]\n🔗 [URL]\n\n🎒 [Secondary feature need] → [Product]\n🔗 [URL]\n\n📱 [Third feature need] → [Product]\n🔗 [URL]\n\n💵 Best Value → [Product]\n🔗 [URL]\n\n━━━━━━━━━━━━━━\n\nDYNAMIC LANGUAGE RULES:\n- For electronics: mention wattage, ports, compatibility\n- For accessories: mention material, compatibility, durability\n- For apparel: mention fit, material, style\n- For home goods: mention size, material, features\n- Adapt \"need\" categories to product type\n- Use product-specific terminology\n\nFORMATTING CHECKLIST:\n✓ Product names shortened to 50 chars max\n✓ Every product has Amazon URL with 🔗\n✓ Use *bold* only for section headers\n✓ Plain text for everything else\n✓ URLs on separate lines after product\n✓ Real data from JSON (prices, ratings, reviews, sales)\n✓ Specific features, not generic \"high quality\"\n✓ Total output under 2500 characters\n\nEXTRACT FROM DATA:\n- Use {{ $json.top_picks[0].title }} for product names\n- Use {{ $json.top_picks[0].url }} for Amazon links\n- Use {{ $json.top_picks[0].price }} for prices\n- Use {{ $json.top_picks[0].rating }} for ratings\n- Use {{ $json.top_picks[0].reviews }} for review counts\n- Use {{ $json.top_picks[0].sales }} for sales volume\n\nStart writing now. Be concise, specific, and dynamic!", "prompt": "=You are a product recommendation expert analyzing {{ $json.query }}.\n\nAVAILABLE DATA:\n- Total Products: {{ $json.total }}\n- Price Range: ${{ $json.stats.min_price }} - ${{ $json.stats.max_price }} (avg: ${{ $json.stats.avg_price }})\n- Average Rating: {{ $json.stats.avg_rating }}/5\n- Total Reviews: {{ $json.stats.total_reviews }}\n\nCATEGORIES:\n- Top Picks: {{ $json.top_picks.length }}\n- Budget (<$30): {{ $json.budget_options.length }}\n- Premium ($50+): {{ $json.premium_options.length }}\n- Best Value: {{ $json.best_value.length }}\n- Most Popular: {{ $json.most_popular.length }}\n\nCRITICAL RULES:\n1. MAX 2500 characters\n2. Use TELEGRAM MARKDOWN (legacy):\n - *bold* for headers only\n - No special escaping needed\n - Plain URLs on new lines\n3. SHORTEN product names to max 50 chars\n4. Each product MUST include its Amazon URL\n5. Be DYNAMIC - adapt language to product type\n6. VARIED symbols: 💵📊🔥💰⚡🎒📱🍎✓\n\nOUTPUT FORMAT:\n\n*🏆 TOP 3 PICKS*\n\n*1. [Short Product Name]*\n💵 $[XX] | 📊 [X.X]/5 ([XX]K reviews) | 🔥 [Sales]\n✓ [Key unique feature in 5-8 words]\n✓ [Value reason in 10-15 words]\n🔗 [Full Amazon URL]\n\n*2. [Short Product Name]*\n💵 $[XX] | 📊 [X.X]/5 ([XX]K reviews) | 🔥 [Sales]\n✓ [Key unique feature in 5-8 words]\n✓ [Value reason in 10-15 words]\n🔗 [Full Amazon URL]\n\n*3. [Short Product Name]*\n💵 $[XX] | 📊 [X.X]/5 ([XX]K reviews) | 🔥 [Sales]\n✓ [Key unique feature in 5-8 words]\n✓ [Value reason in 10-15 words]\n🔗 [Full Amazon URL]\n\n━━━━━━━━━━━━━━\n\n*💰 BEST BUDGET*\n[Product Name - shortened]\n💵 $[XX] (was $[Original]) | 📊 [X.X]/5 | 💰 Save $[XX]\nPerfect for: [User type in 8-12 words]\nTrade-off: [What's missing vs premium in 6-10 words]\n🔗 [Full Amazon URL]\n\n*💎 BEST PREMIUM*\n[Product Name - shortened]\n💵 $[XX] | 📊 [X.X]/5 ([XX] reviews)\nWorth it: [Premium features in 12-15 words]\nBest for: [Specific user scenario in 8-10 words]\n🔗 [Full Amazon URL]\n\n━━━━━━━━━━━━━━\n\n*📊 QUICK STATS*\n\n💸 Cheapest: [Name] - $[XX]\n⭐ Top Rated: [Name] - [X.X]/5\n🔥 Most Popular: [Name] - [Sales]\n💰 Best Deal: [Name] - [XX]% off\n\n━━━━━━━━━━━━━━\n\n*🎯 PICK BY NEED*\n\n⚡ [Primary feature need] → [Product]\n🔗 [URL]\n\n🎒 [Secondary feature need] → [Product]\n🔗 [URL]\n\n📱 [Third feature need] → [Product]\n🔗 [URL]\n\n💵 Best Value → [Product]\n🔗 [URL]\n\n━━━━━━━━━━━━━━\n\nDYNAMIC LANGUAGE RULES:\n- For electronics: mention wattage, ports, compatibility\n- For accessories: mention material, compatibility, durability\n- For apparel: mention fit, material, style\n- For home goods: mention size, material, features\n- Adapt \"need\" categories to product type\n- Use product-specific terminology\n\nFORMATTING CHECKLIST:\n✓ Product names shortened to 50 chars max\n✓ Every product has Amazon URL with 🔗\n✓ Use *bold* only for section headers\n✓ Plain text for everything else\n✓ URLs on separate lines after product\n✓ Real data from JSON (prices, ratings, reviews, sales)\n✓ Specific features, not generic \"high quality\"\n✓ Total output under 2500 characters\n\nEXTRACT FROM DATA:\n- Use {{ $json.top_picks[0].title }} for product names\n- Use {{ $json.top_picks[0].url }} for Amazon links\n- Use {{ $json.top_picks[0].price }} for prices\n- Use {{ $json.top_picks[0].rating }} for ratings\n- Use {{ $json.top_picks[0].reviews }} for review counts\n- Use {{ $json.top_picks[0].sales }} for sales volume\n\nStart writing now. Be concise, specific, and dynamic!", "batching": {}, "provider": "openai", "promptType": "define", "approximated": true }, "position": [ 2224, 480 ] }, { "id": "50f0c091-0af8-4256-8431-795e9cc17ce6", "name": "Send Final Response", "type": "integration", "params": { "text": "={{ $json.text }}", "chatId": "={{ $('Extract Chat & Query').item.json.chatId }}", "service": "telegram", "operation": "read", "additionalFields": { "parse_mode": "Markdown" } }, "position": [ 2576, 480 ] }, { "id": "9208513e-437e-4274-8715-87cb477323cf", "name": "Validate Product Input", "type": "llm", "params": { "text": "={{ $json.message.text }}", "prompt": "={{ $json.message.text }}", "batching": {}, "messages": { "messageValues": [ { "message": "=You are a product validator. \nCheck if the user input contains a valid product name. \n- If the input is ambiguous or includes extra descriptive words (e.g. color, speed, or adjectives), extract only the **core product name**. \n- If there is no identifiable product, mark it as invalid. \n\nExample: \nInput: \"I want a blue fast charging iPhone 11 256GB\" \nOutput: \n{\n \"keyword\": \"iPhone 11 256GB\",\n \"status\": \"VALID\"\n}\n\nExample: \nInput: \"I want something nice\" \nOutput: \n{\n \"keyword\": \"\",\n \"status\": \"INVALID\"\n}\n\nReturn the result **exactly** in this JSON structure:\n{\n \"keyword\": \"\",\n \"status\": \"VALID\" or \"INVALID\"\n}\n" } ] }, "provider": "openai", "promptType": "define", "approximated": true, "hasOutputParser": true }, "position": [ 928, 528 ] }, { "id": "02a37df9-d6ff-434e-843d-933ad2bdd6c5", "name": "Parse Validation Output", "type": "passthrough", "params": { "mode": "noOp", "jsonSchemaExample": "{\n \"keyword\": \"\",\n \"status\": \"VALID or INVALID\"\n}" }, "position": [ 1072, 688 ] }, { "id": "116fcd7b-6fa1-44e4-bb30-05d6a45a1ce1", "name": "Check Product Validity", "type": "if", "params": { "options": {}, "conditions": { "options": { "version": 2, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "1753216c-c3c5-4617-a940-f5049cf2679e", "operator": { "name": "filter.operator.equals", "type": "string", "operation": "equals" }, "leftValue": "={{ $json.output.status }}", "rightValue": "=VALID" } ] } }, "position": [ 1280, 528 ] }, { "id": "16886532-c324-4c53-9341-6d3484ca2ec9", "name": "Send Invalid Message", "type": "integration", "params": { "text": "=no product detected on your input, please try again", "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}", "service": "telegram", "operation": "read", "additionalFields": { "parse_mode": "Markdown", "appendAttribution": false } }, "position": [ 1536, 672 ] }, { "id": "4c71756c-42d1-436b-8583-2aa39e20376d", "name": "Send Processing Status", "type": "integration", "params": { "text": "=Processing your input...", "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}", "service": "telegram", "operation": "read", "additionalFields": { "parse_mode": "Markdown", "appendAttribution": false } }, "position": [ 1168, 352 ] }, { "id": "f913fe74-be48-4a9a-8f04-0f7cf536f5c3", "name": "Send Valid Confirmation", "type": "integration", "params": { "text": "=Input Valid | keyword: {{ $json.output.keyword }}\n\nprocessing your request...", "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}", "service": "telegram", "operation": "read", "additionalFields": { "parse_mode": "HTML", "appendAttribution": false } }, "position": [ 1536, 288 ] }, { "id": "636f1157-1f2a-44d8-b6c7-8e6cb4aea604", "name": "Gemini 2.5 Flash", "type": "llm", "params": { "options": {}, "provider": "google" }, "position": [ 2368, 640 ] }, { "id": "07556ea8-f88a-4720-84b2-cfbc651c9a05", "name": "Give Delay", "type": "passthrough", "params": { "mode": "noOp", "amount": 2 }, "position": [ 976, 352 ] }, { "id": "fd75b467-fc1f-4389-a169-4dee1e67c218", "name": "Format Error Notification", "type": "code", "params": { "jsCode": "// Optimized error handler - clean & informative\nconst errorData = $input.first().json;\n\nfunction getNestedValue(obj, path, defaultValue = 'Unknown') {\n return path.split('.').reduce((curr, prop) => \n curr?.[prop], obj) || defaultValue;\n}\n\nconst workflowName = getNestedValue(errorData, 'workflow.name', 'Unknown Workflow');\nconst nodeName = getNestedValue(errorData, 'execution.error.node.name', 'Unknown Node');\nconst errorMessage = getNestedValue(errorData, 'execution.error.message', 'No error message');\nconst timestamp = getNestedValue(errorData, 'execution.startedAt', new Date().toISOString());\nconst executionId = getNestedValue(errorData, 'execution.id', 'Unknown');\n\n// Tangkap error details\nconst errorObj = errorData.execution?.error || {};\nconst errorDescription = errorObj.description || '';\nconst errorHttpCode = errorObj.httpCode || '';\n\n// Stack trace - ambil HANYA baris pertama yang paling penting\nconst errorStack = errorObj.stack || '';\nconst mainError = errorStack.split('\\n')[0] || '';\n\n// Format detail yang clean\nlet errorDetails = [];\nif (errorDescription && errorDescription !== errorMessage) {\n errorDetails.push(errorDescription);\n}\nif (errorHttpCode) {\n errorDetails.push(`HTTP ${errorHttpCode}`);\n}\n\nconst detailText = errorDetails.length > 0 \n ? errorDetails.join(' | ') \n : 'No additional details';\n\n// Main error dari stack (tanpa \"NodeApiError: \" prefix)\nconst cleanMainError = mainError.replace(/^(NodeApiError|Error):\\s*/, '').trim();\n\n// Build message - COMPACT VERSION\nconst message = `🚨 WORKFLOW ERROR\\n\\n` +\n `📋 ${workflowName}\\n` +\n `⚙️ Node: ${nodeName}\\n\\n` +\n `❌ ${errorMessage}\\n` +\n `💡 ${detailText}\\n\\n` +\n `🕐 ${new Date(timestamp).toLocaleString('id-ID', { \n day: '2-digit', \n month: 'short', \n hour: '2-digit', \n minute: '2-digit' \n })}\\n` +\n `🔗 Exec: ${executionId}`;\n\nreturn {\n json: {\n message: message\n }\n};" }, "position": [ 992, 1024 ] }, { "id": "2cca63a2-4999-48c6-8f7b-c8871a8a9ccb", "name": "Notify Admin", "type": "integration", "params": { "text": "={{ $json.message }}", "chatId": "YOUR-CHAT-ID", "service": "telegram", "operation": "read", "additionalFields": { "parse_mode": "HTML" } }, "position": [ 1216, 1024 ] } ] }

AI-powered Amazon product recommendations via Decodo, Telegram and Gemini 2.5