{ "nodes": [ { "parameters": { "updates": [ "message" ], "additionalFields": {} }, "type": "n8n-nodes-base.telegramTrigger", "typeVersion": 1.2, "position": [ -13632, 1584 ], "id": "cbb919ec-160f-439d-b2d4-fd581ed0ecd5", "name": "Telegram Trigger", "webhookId": "de03b2ad-85a1-463a-9a1a-6e3c307de84a" }, { "parameters": { "conditions": { "options": { "caseSensitive": false, "leftValue": "", "typeValidation": "loose", "version": 3 }, "conditions": [ { "id": "text-exists-check", "leftValue": "={{ $json.message.text }}", "rightValue": "", "operator": { "type": "string", "operation": "exists", "singleValue": true } }, { "id": "text-length-check", "leftValue": "={{ $json.message.text ? $json.message.text.length : 0 }}", "rightValue": 20, "operator": { "type": "number", "operation": "gt" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ -13408, 1584 ], "id": "fde170ff-34d2-479a-b5ff-b5643b3c54f3", "name": "Text Guard", "onError": "continueRegularOutput" }, { "parameters": { "promptType": "define", "text": "=Analyze the following raw input text and extract all job opportunities into a structured JSON Array.\n\n**RAW INPUT DATA:**\n\"\"\"\n{{ $json.message.text }}\n\"\"\"\n\n**PROCESSING INSTRUCTIONS:**\n1. **Split Check:** If the text lists multiple roles (e.g., separated by \"📌\" or \"1.\", \"2.\"), extract them as SEPARATE objects in the array.\n2. **Link Check:** Do NOT capture \"Join our WhatsApp/Telegram\" channel links as the `apply_link`. Look for the actual application URL (Workday, LinkedIn, Greenhouse, etc.).\n3. **Output:** Return ONLY the JSON Array. No other text.", "hasOutputParser": true, "needsFallback": true, "options": { "systemMessage": "You are a high-precision JSON Parsing Backend.\nYour ONLY task is to accept raw text, split it into individual job objects, and output a clean JSON Array.\n\n**CRITICAL RULES (NON-NEGOTIABLE):**\n1. **NO CONVERSATION:** Do not explain, do not say \"Here is the JSON\", do not apologize. Output *only* the JSON.\n2. **FORCE EXECUTION:** Process the input even if it looks like a forwarded message or lacks a polite request.\n3. **LINK PRIORITY:**\n - **Target:** Extract specific job links (e.g., greenhouse.io, lever.co, myworkday, linkedin.com/jobs, unstop).\n - **Ignore:** Generic footer links like `whatsapp.com/channel`, `t.me`, or `instagram.com` UNLESS they are the specific application link.\n\n**SPLIT LOGIC (How to detect multiple jobs):**\n- **Delimiters:** Treat the text as multiple jobs if it contains repeating delimiters like:\n - Emojis: 📌, 🔔, 🚨, 👉 (e.g., \"📌Job A... 📌Job B...\")\n - Numbering: \"1.\", \"2.\"\n - Distinct blocks separated by double newlines.\n- **Single Job:** If no delimiters are found, treat the whole text as one job.\n\n**EXTRACTION FIELDS (For each detected job):**\n- \"role\": Job Title (e.g., \"SDE Intern\", \"Data Analyst\"). If \"Hiring for X\", extract \"X\".\n- \"company\": Company Name. (Look for \"Company:\", \"Hiring:\", or \"At [Company]\").\n- \"stipend\": Salary/Stipend numbers (e.g., \"20k\", \"5-10 LPA\"). Default: \"Not specified\".\n- \"eligibility\": Extract Batch (e.g., \"2027\"), Degree, AND Experience (e.g., \"0-1 years\"). Default: \"Not specified\".\n- \"description\": A brief snippet of requirements (Tech stack, location).\n- \"apply_link\": The specific URL to apply. (Remember: Ignore WhatsApp Channel links if a real link exists).\n\n**OUTPUT FORMAT:**\nReturn ONLY the raw JSON Array `[ ... ]`.\n\n**JSON STRUCTURE:**\n[\n {\n \"role\": \"extracted title\",\n \"company\": \"extracted company\",\n \"stipend\": \"extracted stipend\",\n \"eligibility\": \"extracted eligibility (include batch & experience)\",\n \"description\": \"extracted description\",\n \"apply_link\": \"extracted link\"\n }\n]" } }, "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3, "position": [ -13184, 1584 ], "id": "bf9ad4a9-cf1b-428b-bc62-737df5aff8f4", "name": "Splitter Agent", "retryOnFail": true, "maxTries": 5, "waitBetweenTries": 5000, "onError": "continueErrorOutput" }, { "parameters": { "jsCode": "// 1. Get the raw output from the AI model\nconst rawContent = $input.first().json.output || \"\";\n\n// 2. Clean the string: Remove Markdown code blocks (```json ... ```)\nconst cleanJson = rawContent.replace(/^```json\\s*/i, \"\").replace(/\\s*```$/, \"\");\n\n// 3. Parse the string into a real JavaScript Array\nlet jobsArray = [];\ntry {\n jobsArray = JSON.parse(cleanJson);\n} catch (error) {\n console.log(\"JSON Parse Error:\", error);\n jobsArray = [];\n}\n\n// 4. Return separate items for n8n to process\nreturn jobsArray.map(job => {\n return {\n json: job\n };\n});" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -12784, 1392 ], "id": "f2cad12a-b8fb-4e8f-9581-7336506396fe", "name": "JSON Format Fixer" }, { "parameters": { "options": {} }, "type": "n8n-nodes-base.splitInBatches", "typeVersion": 3, "position": [ -12560, 1392 ], "id": "07919b5e-6d52-48a6-8595-da5c507edcf2", "name": "Loop Over Each Link" }, { "parameters": { "method": "POST", "url": "https://your-deployment/firecrawl/v1/scrape", "sendBody": true, "bodyParameters": { "parameters": [ { "name": "url", "value": "={{ $json.apply_link }}" } ] }, "options": {} }, "id": "9741bff9-9ec1-487b-9721-558d395497dd", "name": "Firecrawl Scrape", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ -12336, 1056 ], "alwaysOutputData": true, "retryOnFail": true, "onError": "continueRegularOutput" }, { "parameters": { "jsCode": "// ============================================================\n// Pre-Check Node — FIXED for blocked ATS sites (Workday etc.)\n// ============================================================\n\nconst CONFIG = {\n wrong_years: /\\b(2020|2021|2022|2023|2024|2025|2026)\\b/,\n target_year: /2027/,\n blocked_domains: []\n};\n\nreturn items.map(item => {\n const rawMarkdown = (item.json.data?.markdown || \"\").substring(0, 30000);\n const telegramText = $('Telegram Trigger').first().json.message.text || \"\";\n const url = (item.json.apply_link || \"\").toLowerCase();\n const isBlockedDomain = CONFIG.blocked_domains.some(domain => url.includes(domain));\n const scrapeSucceeded = rawMarkdown.length > 150 && !isBlockedDomain;\n const scrape_failed = !scrapeSucceeded;\n\n const scraped_markdown = scrapeSucceeded\n ? rawMarkdown\n : `[Scraping unavailable — site blocked automated access (${isBlockedDomain ? 'known blocked ATS domain' : 'empty response'}). Using original Telegram job post for analysis below.]\\n\\n${telegramText}`;\n\n const combinedText = [\n item.json.role,\n item.json.company,\n item.json.eligibility,\n scraped_markdown,\n telegramText\n ].filter(Boolean).join(\" \").toLowerCase();\n\n let status = \"PASS\";\n let rejectReason = \"N/A\";\n\n if (CONFIG.wrong_years.test(combinedText) && !CONFIG.target_year.test(combinedText)) {\n status = \"REJECT\";\n rejectReason = \"Hard Filter: Explicit Old Batch (Mentioned older years but not 2027)\";\n }\n\n const debug = {\n markdown_length: rawMarkdown.length,\n scrape_failed: scrape_failed,\n using_fallback: scrape_failed,\n is_blocked_domain: isBlockedDomain,\n apply_link: item.json.apply_link || \"\",\n telegram_text_found: !!telegramText,\n years_found: combinedText.match(CONFIG.wrong_years) || \"None\",\n target_found: CONFIG.target_year.test(combinedText)\n };\n\n return {\n json: {\n ...item.json,\n scraped_markdown: scraped_markdown,\n pre_filter_status: status,\n rejection_reason: rejectReason,\n debug_log: debug\n }\n };\n});" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -12112, 1056 ], "id": "755eddf9-3ba6-47a6-a746-538ae602757c", "name": "Pre-Check", "alwaysOutputData": true, "onError": "continueRegularOutput" }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "42b354f7-17d1-462e-bed7-54a0d225053c", "leftValue": "={{ $json.pre_filter_status }}", "rightValue": "PASS", "operator": { "type": "string", "operation": "equals" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ -11888, 1056 ], "id": "7fa4777f-cc53-453d-9a96-9a79465241ad", "name": "For 2027?", "alwaysOutputData": false, "onError": "continueRegularOutput" }, { "parameters": { "promptType": "define", "text": "=Process the following job opportunity data and extract the structured output.\n\n**TASK:**\n1. Analyze the \"JOB PAGE MARKDOWN\" below to determine eligibility.\n2. IF the text is missing the Batch Year (e.g., just says \"Student\" or \"Intern\"), use `serpapi_search` to verify if it is for 2027 graduates.\n3. NOTE: If the JOB PAGE MARKDOWN starts with \"[Scraping unavailable\", it means the job page could not be scraped (blocked ATS like Workday/Greenhouse). In this case, rely entirely on the Telegram text provided after that label and the INPUT DATA fields above.\n\n**INPUT DATA:**\nTitle: {{ $('JSON Format Fixer').item.json.role }}\nCompany: {{ $('JSON Format Fixer').item.json.company }}\nEligibilty : {{ $('JSON Format Fixer').item.json.eligibility }}\nStipend : {{ $('JSON Format Fixer').item.json.stipend }}\nLink: {{ $('JSON Format Fixer').item.json.apply_link }}\n\n**JOB PAGE MARKDOWN (SOURCE):**\n\"\"\"\n{{ $json.scraped_markdown }}\n\"\"\"\n\n**OUTPUT REQUIREMENTS:**\n- Verify strict eligibility for **Batch of 2027** (Pre-final year).\n- Return the final JSON using the \"Final Answer\" format defined in the system message.", "hasOutputParser": true, "needsFallback": true, "options": { "systemMessage": "You are a backend JSON Data Processing Engine.\nYour ONLY function is to analyze job data and output a JSON response.\n\n**CORE OBJECTIVE:**\nIdentify valid **TECHNICAL** internship opportunities for **Pre-final Year Students (Batch of 2027)**.\n\n**STRICT DEFINITIONS:**\n- **Valid Role:** \"Intern\", \"Summer Analyst\", \"Trainee\" (only if <1 yr exp).\n- **Invalid Role:** \"Full Time\", \"FTE\", \"Software Engineer\" (without 'Intern'), \"Associate\", \"SDE-1\".\n- **Valid Batch:** 2027, Pre-final year, Penultimate year.\n\n**SCRAPING FAILURE HANDLING:**\n- If the JOB PAGE MARKDOWN starts with \"[Scraping unavailable\", the job site blocked automated access (common for Workday, Greenhouse, Lever).\n- In this case, base your analysis ONLY on the INPUT DATA fields (Title, Company, Eligibility, Stipend, Link) and the Telegram text included in the fallback message.\n- Do NOT reject a job solely because the page couldn't be scraped. Apply the same eligibility logic using available text.\n\n**EXECUTION PROTOCOL (STRICT ORDER - DO NOT SKIP):**\n\n**STEP 1: MANDATORY DUPLICATE CHECK (BLOCKING)**\n- **Action:** You MUST call the tool `check_duplicate` first.\n- **Input:** Use the job link provided in the prompt.\n- **Logic:**\n - If tool returns `true`: **STOP IMMEDIATELY.** Output `{\"send_whatsapp\": false, \"reason\": \"Duplicate\"}`.\n\n**STEP 2: EXCLUSION LOGIC (THE \"KILL SWITCH\")**\n- Read the Markdown text. If ANY of these are true, **STOP and REJECT**.\n\n - **A. DOMAIN FILTER:**\n - Is the role Finance, HR, Sales, Marketing, Operations, Customer Support?\n - -> **REJECT** (Reason: \"Non-technical\").\n\n - **B. EXPLICIT WRONG BATCH (CRITICAL):**\n - Does the text mention specific years (e.g., \"2023\", \"2024\", \"2025\", \"2026\") BUT NOT \"2027\"?\n - *Example:* \"Hiring 2025 & 2026 grads\" -> **REJECT**.\n - *Example:* \"For 2023/24 batch\" -> **REJECT**.\n - *Logic:* If years are present, 2027 MUST be one of them.\n\n - **C. EXPERIENCE FILTER:**\n - Does it require \"1+ years\", \"1-3 years\", or \"Graduates from [past year]\"?\n - -> **REJECT** (Reason: \"Experience required\").\n\n - **D. FTE TRAP:**\n - Is the title \"Software Engineer\", \"Developer\", or \"SDE\" (with NO mention of \"Intern\" or \"Trainee\")?\n - -> **REJECT** (Reason: \"Full-time role\").\n\n**STEP 3: VALIDATION SCAN (POSITIVE MATCH)**\n- *Only runs if Step 2 passed.*\n- **CHECK A:** Does text contain \"2027\"? -> **VALID**.\n- **CHECK B:** Does text contain \"Pre-final\" or \"Penultimate\"? -> **VALID**.\n- **CHECK C:** Is it a generic \"Intern\" role (e.g., \"SDE Intern\") with NO year mentioned? -> **SEARCH REQUIRED** (Go to Step 4).\n\n**STEP 4: FALLBACK SEARCH (LAST RESORT)**\n- *Only runs if text is ambiguous (e.g., \"SDE Intern\" with no year).*\n- **Action:** Call `serpapi_request`.\n- **Input Schema:** `{ \"query\": \"Company Role 2027 eligibility\" }`\n\n**STEP 5: DEADLINE EXTRACTION**\n- Scan the text for keywords like \"Apply by\", \"Deadline\", \"Last Date\", \"Closes on\", or \"Test Date\".\n- If a date is found, convert it strictly to `YYYY-MM-DD` format (e.g., \"March 15th 2026\" becomes \"2026-03-15\").\n- If no specific date is mentioned, set the JSON value to `null`.\n\n**WHATSAPP MESSAGE TEMPLATE:**\n `*New Internship Alert!*`\n ` `\n `*Title:* `\n `*Company:* `\n `*Eligibility:* `\n `*Deadline:* `\n ` `\n `*Apply Link:* `\n\n**OUTPUT INSTRUCTION:**\nReturn ONLY the raw JSON object inside a code block.\nFinal Answer:\n```json\n{\n \"send_whatsapp\": boolean,\n \"reason\": \"...\",\n \"whatsapp_message\": \"...\",\n \"deadline\": \"YYYY-MM-DD or Not Specified\"\n}" } }, "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3, "position": [ -11568, 880 ], "id": "20e9bdf4-9b99-465a-99a7-528476ee5797", "name": "Analyst Agent", "retryOnFail": true, "waitBetweenTries": 5000, "maxTries": 5, "alwaysOutputData": false, "onError": "continueErrorOutput" }, { "parameters": { "toolDescription": "Performs a Google search to verify internship eligibility. Use this ONLY when the provided text is ambiguous or missing the batch year (e.g., '2027'). CRITICAL: You must provide a specific query string (e.g., 'Google Software Engineer Intern 2027 eligibility').", "method": "POST", "url": "https://your-deployment/webhook/serpapi_search", "sendBody": true, "bodyParameters": { "parameters": [ { "name": "query", "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Value', `The search query string (e.g. 'Company Role 2027 eligibility')`, 'string') }}" } ] }, "options": {} }, "type": "n8n-nodes-base.httpRequestTool", "typeVersion": 4.3, "position": [ -11408, 1104 ], "id": "0699c870-4176-44bb-b1c7-25fa0dbd5318", "name": "serpapi_request" }, { "parameters": { "model": "llama-3.3-70b-versatile", "options": { "temperature": 0.1 } }, "type": "@n8n/n8n-nodes-langchain.lmChatGroq", "typeVersion": 1, "position": [ -11536, 1104 ], "id": "91a1f7de-e8ee-4234-ad74-b8311e8d9651", "name": "Analyst Fallback" }, { "parameters": { "descriptionType": "manual", "toolDescription": "CRITICAL: Call this FIRST. Checks if the job link is already in the database. If it returns any valid item as output, you must STOP immediately and return send_whatsapp: false.", "operation": "get", "dataTableId": { "__rl": true, "value": "yOfWQK9CB3soT3Ai", "mode": "list", "cachedResultName": "Internship Alerts", "cachedResultUrl": "/projects/0aENaaiAf9dL9Hyo/datatables/yOfWQK9CB3soT3Ai" }, "filters": { "conditions": [ { "keyName": "Application_Link", "keyValue": "={{ $('Loop Over Each Link').item.json.apply_link }}" } ] }, "returnAll": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Return_All', ``, 'boolean') }}" }, "type": "n8n-nodes-base.dataTableTool", "typeVersion": 1.1, "position": [ -11280, 1104 ], "id": "e67b2d61-a383-4ea7-b00c-a111ba9d4313", "name": "check_duplicate" }, { "parameters": { "jsCode": "// 1. Get the raw text output safely\nconst rawText = items[0]?.json?.output;\n\nif (!rawText) {\n return [{ json: { error: \"No output received from Analyst Agent\" } }];\n}\n\n// 2. Try to find JSON inside markdown blocks\nconst markdownMatch = rawText.match(/```json\\s*([\\s\\S]*?)\\s*```/);\n\n// 3. Robust JSON Extraction\nconst firstOpen = rawText.indexOf('{');\nconst lastClose = rawText.lastIndexOf('}');\n\nlet finalJson = {};\n\ntry {\n if (markdownMatch) {\n finalJson = JSON.parse(markdownMatch[1]);\n } else if (firstOpen !== -1 && lastClose !== -1 && lastClose > firstOpen) {\n const jsonString = rawText.substring(firstOpen, lastClose + 1);\n finalJson = JSON.parse(jsonString);\n } else {\n throw new Error(\"No JSON structure found\");\n }\n} catch (error) {\n finalJson = {\n send_whatsapp: false,\n reason: \"JSON Parsing Failed\",\n org_text: $('Telegram Trigger').first().json.message.text || \"Text unavailable\",\n error_details: error.message,\n raw_output: rawText\n };\n}\n\nreturn [{ json: finalJson }];" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -11072, 784 ], "id": "2284da05-a867-4a6d-8542-00cd1aadf2c4", "name": "Output Parser" }, { "parameters": { "operation": "get", "dataTableId": { "__rl": true, "value": "yOfWQK9CB3soT3Ai", "mode": "list", "cachedResultName": "Internship Alerts", "cachedResultUrl": "/projects/0aENaaiAf9dL9Hyo/datatables/yOfWQK9CB3soT3Ai" }, "filters": { "conditions": [ { "keyName": "Application_Link", "keyValue": "={{ $('Loop Over Each Link').item.json.apply_link }}" } ] }, "limit": 1 }, "type": "n8n-nodes-base.dataTable", "typeVersion": 1.1, "position": [ -10848, 784 ], "id": "9c97d24f-d88e-46e5-b045-246329c09890", "name": "Check for duplicate valid", "alwaysOutputData": true }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "7c4709a1-e1dd-4021-99f2-f636a049bedd", "leftValue": "={{ $('Output Parser').item.json.send_whatsapp }}", "rightValue": true, "operator": { "type": "boolean", "operation": "equals" } }, { "id": "9fd508d8-b394-442c-9dca-f730575edb3e", "leftValue": "={{ $json.title }}", "rightValue": "", "operator": { "type": "string", "operation": "notExists", "singleValue": true } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.2, "position": [ -10624, 784 ], "id": "bd5f96e5-51ca-4bb6-89a3-ccde9e80aca5", "name": "Not Duplicate?", "retryOnFail": true }, { "parameters": { "conditions": { "options": { "caseSensitive": false, "leftValue": "", "typeValidation": "loose", "version": 3 }, "conditions": [ { "id": "a4622224-cc41-4d61-9b80-1bfd67e03422", "leftValue": "={{ $('Output Parser').item.json.deadline }}", "rightValue": "Not Specified", "operator": { "type": "string", "operation": "notEquals" } } ], "combinator": "and" }, "looseTypeValidation": true, "options": { "ignoreCase": true } }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ -10400, 736 ], "id": "6874a22f-a2da-4d37-a9fb-380f63896a7f", "name": "Deadline Exists?", "onError": "continueRegularOutput" }, { "parameters": { "calendar": { "__rl": true, "value": "your-email@gmail.com", "mode": "list", "cachedResultName": "your-email@gmail.com" }, "start": "={{ $('Output Parser').item.json.deadline }}T09:00:00Z", "end": "={{ $('Output Parser').item.json.deadline }}T10:00:00Z", "additionalFields": { "description": "=Link : {{ $('JSON Format Fixer').item.json.apply_link }}", "summary": "=🚨 APPLY TODAY: {{ $('JSON Format Fixer').item.json.role }} at {{ $('JSON Format Fixer').item.json.company }}" } }, "type": "n8n-nodes-base.googleCalendar", "typeVersion": 1.3, "position": [ -10176, 816 ], "id": "0c5e1fa9-97c1-4ac7-95ae-f8225f688412", "name": "Add event reminder", "onError": "continueRegularOutput" }, { "parameters": { "documentId": { "__rl": true, "value": "YOUR_SPREADSHEET_ID", "mode": "list", "cachedResultName": "InternshipSites", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/YOUR_SPREADSHEET_ID/edit?usp=drivesdk" }, "sheetName": { "__rl": true, "value": 198098392, "mode": "list", "cachedResultName": "Mobile Numbers", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/YOUR_SPREADSHEET_ID/edit#gid=198098392" }, "options": {} }, "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ -9952, 736 ], "id": "1f81c312-7f1d-4ffd-966d-05f00e845f8c", "name": "Get Mobile Numbers" }, { "parameters": { "options": {} }, "type": "n8n-nodes-base.splitInBatches", "typeVersion": 3, "position": [ -9728, 736 ], "id": "33af2cb8-d657-4bce-ac02-060390d4da00", "name": "Loop Over Items", "executeOnce": false }, { "parameters": { "operation": "append", "documentId": { "__rl": true, "value": "YOUR_SPREADSHEET_ID", "mode": "list", "cachedResultName": "InternshipSites", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/YOUR_SPREADSHEET_ID/edit?usp=drivesdk" }, "sheetName": { "__rl": true, "value": 607067211, "mode": "list", "cachedResultName": "True Classification", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/YOUR_SPREADSHEET_ID/edit#gid=607067211" }, "columns": { "mappingMode": "defineBelow", "value": { "Timestamp": "={{ $now }}", "Telegram Message": "={{ $('Telegram Trigger').item.json.message.text }}", "Title": "={{ $('Loop Over Each Link').item.json.role }}", "Company Name": "={{ $('Loop Over Each Link').item.json.company }}", "Eligibility": "={{ $('Loop Over Each Link').item.json.eligibility }}", "Application Link": "={{ $('Loop Over Each Link').item.json.apply_link }}", "Status": "Pending" }, "matchingColumns": [], "schema": [ { "id": "Timestamp", "displayName": "Timestamp", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Telegram Message", "displayName": "Telegram Message", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Title", "displayName": "Title", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Company Name", "displayName": "Company Name", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Eligibility", "displayName": "Eligibility", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Application Link", "displayName": "Application Link", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Status", "displayName": "Status", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true, "removed": false } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ -9504, 688 ], "id": "373e5443-4fb4-49dc-993e-bd8eda903a73", "name": "Append Valid", "executeOnce": true, "retryOnFail": true }, { "parameters": { "method": "POST", "url": "https://your-deployment/send", "sendBody": true, "bodyParameters": { "parameters": [ { "name": "to", "value": "=+{{ $json['Phone Number'] }}" }, { "name": "message", "value": "={{ $('Output Parser').item.json.whatsapp_message }}" } ] }, "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.3, "position": [ -9504, 880 ], "id": "e4dd311a-1bf9-4bf4-bdb0-3fff91a9c8a1", "name": "Send Whatsapp Message", "retryOnFail": true, "waitBetweenTries": 3000 }, { "parameters": { "dataTableId": { "__rl": true, "value": "yOfWQK9CB3soT3Ai", "mode": "list", "cachedResultName": "Internship Alerts", "cachedResultUrl": "/projects/0aENaaiAf9dL9Hyo/datatables/yOfWQK9CB3soT3Ai" }, "columns": { "mappingMode": "defineBelow", "value": { "title": "={{ $('Loop Over Each Link').item.json.role }}", "Eligibilty": "={{ $('Loop Over Each Link').item.json.eligibility }}", "Application_Link": "={{ $('Loop Over Each Link').item.json.apply_link }}", "Company_Name": "={{ $('Loop Over Each Link').item.json.company }}" }, "matchingColumns": [ "Internship" ], "schema": [ { "id": "title", "displayName": "title", "required": false, "defaultMatch": false, "display": true, "type": 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