{ "edges": [ { "to": "4a59236b-8d34-490c-8253-356db1adcd4f", "from": "36269d3c-8615-4cc9-b84e-146f89a92ddb", "toPort": "0", "fromPort": "0" }, { "to": "364cbfe9-aedc-4bae-b67f-26f371aa86a0", "from": "093a5c93-4f3a-4572-b6a6-e4a1918584fc", "toPort": "0", "fromPort": "0" }, { "to": "98f7dfd0-d690-4fdc-9ddd-ef3e15fc3bdb", "from": "093a5c93-4f3a-4572-b6a6-e4a1918584fc", "toPort": "0", "fromPort": "1" }, { "to": "0b9ce595-7d22-46c9-80b9-cec8f930a152", "from": "8a1e7307-e39c-4830-9b27-45a857d79598", "toPort": "0", "fromPort": "0" }, { "to": "1b31fddc-ba98-462c-b85e-e67440441926", "from": "8c1f4352-064f-420e-8b24-68c4a127fea1", "toPort": "0", "fromPort": "0" }, { "to": "34acf446-4393-46e4-9784-f0ed59e3c725", "from": "1e3d73b1-f241-49da-be52-8b44d3e54f1a", "toPort": "0", "fromPort": "ai_languageModel" }, { "to": "34acf446-4393-46e4-9784-f0ed59e3c725", "from": "a5720f62-a4e6-4737-a4c8-e2ae8b914b4a", "toPort": "0", "fromPort": "0" }, { "to": "a5720f62-a4e6-4737-a4c8-e2ae8b914b4a", "from": "0b9ce595-7d22-46c9-80b9-cec8f930a152", "toPort": "0", "fromPort": "0" }, { "to": "8a1e7307-e39c-4830-9b27-45a857d79598", "from": "e74acfd0-5f82-4ffa-840d-113b9d6e3c52", "toPort": "0", "fromPort": "0" }, { "to": "8c1f4352-064f-420e-8b24-68c4a127fea1", "from": "98f7dfd0-d690-4fdc-9ddd-ef3e15fc3bdb", "toPort": "0", "fromPort": "0" }, { "to": "36269d3c-8615-4cc9-b84e-146f89a92ddb", "from": "6a569f42-5944-4096-88b8-8a2cb1011bf7", "toPort": "0", "fromPort": "0" }, { "to": "bb290e42-ed39-4ff0-8bf4-5c4c97469b1f", "from": "34acf446-4393-46e4-9784-f0ed59e3c725", "toPort": "0", "fromPort": "0" }, { "to": "e74acfd0-5f82-4ffa-840d-113b9d6e3c52", "from": "4a59236b-8d34-490c-8253-356db1adcd4f", "toPort": "0", "fromPort": "0" }, { "to": "34acf446-4393-46e4-9784-f0ed59e3c725", "from": "dca5260c-583a-4f24-ac9c-8e0115ce5a7e", "toPort": "0", "fromPort": "ai_outputParser" }, { "to": "093a5c93-4f3a-4572-b6a6-e4a1918584fc", "from": "bb290e42-ed39-4ff0-8bf4-5c4c97469b1f", "toPort": "0", "fromPort": "0" }, { "to": "6a569f42-5944-4096-88b8-8a2cb1011bf7", "from": "2430890c-ac15-4f7c-b8cc-f5bf75848c1a", "toPort": "0", "fromPort": "0" } ], "nodes": [ { "id": "6a569f42-5944-4096-88b8-8a2cb1011bf7", "name": "⚙️ Configuration", "type": "set", "params": { "options": {}, "assignments": { "assignments": [ { "id": "config-drive-folder", "name": "DRIVE_ROOT_FOLDER_ID", "type": "string", "value": "YOUR_GOOGLE_DRIVE_FOLDER_ID" }, { "id": "config-sheet-id", "name": "SHEET_ID", "type": "string", "value": "YOUR_GOOGLE_SHEET_ID" }, { "id": "config-recruiter-email", "name": "RECRUITER_EMAIL", "type": "string", "value": "user@example.com" }, { "id": "config-ops-email", "name": "OPS_EMAIL", "type": "string", "value": "user@example.com" }, { "id": "config-sender-email", "name": "SENDER_EMAIL", "type": "string", "value": "user@example.com" }, { "id": "config-score-threshold", "name": "SCORE_THRESHOLD", "type": "number", "value": 75 }, { "id": "config-imap-subject-filter", "name": "IMAP_SUBJECT_FILTER", "type": "string", "value": "New application for" } ] } }, "position": [ 976, 1008 ] }, { "id": "2430890c-ac15-4f7c-b8cc-f5bf75848c1a", "name": "IMAP Email Trigger (Indeed)", "type": "trigger", "params": { "kind": "n8n-nodes-base.emailReadImap", "options": { "customEmailConfig": "[\"UNSEEN\"]" }, "postProcessAction": "nothing", "downloadAttachments": true }, "position": [ 816, 1008 ] }, { "id": "4a59236b-8d34-490c-8253-356db1adcd4f", "name": "Extract Email Metadata", "type": "code", "params": { "jsCode": "// ═══════════════════════════════════════════════════\n// EXTRACT EMAIL METADATA FROM INDEED\n// ═══════════════════════════════════════════════════\nconst items = $input.all();\nconst output = [];\n\nfor (const item of items) {\n const subject = item.json.subject || '';\n const from = item.json.from || '';\n const date = item.json.date || new Date().toISOString();\n \n // Regex on Indeed subject: \"New application for X - Y\"\n // ⚠️ Adapt this regex to match your Indeed email language/format\n const positionMatch = subject.match(/per\\s+(.+?)\\s+-/i);\n const candidateMatch = subject.match(/-\\s*(.+)$/);\n \n const position = positionMatch ? positionMatch[1].trim() : 'Unknown position';\n const candidateName = candidateMatch ? candidateMatch[1].trim() : 'Unknown candidate';\n \n // Filter valid attachments (PDF/DOCX only)\n const attachments = item.binary || {};\n const attachmentKeys = Object.keys(attachments).filter(k => {\n const mime = attachments[k].mimeType || '';\n return mime.includes('pdf') || mime.includes('word') || mime.includes('document');\n });\n \n if (attachmentKeys.length === 0) {\n continue; // Skip emails without a CV attachment\n }\n \n for (const key of attachmentKeys) {\n const executionStart = Date.now();\n output.push({\n json: {\n _meta: { executionStart },\n subject,\n from,\n date,\n position,\n candidateName,\n attachmentKey: key,\n fileName: attachments[key].fileName || `cv_${Date.now()}.pdf`,\n mimeType: attachments[key].mimeType\n },\n binary: {\n cv: attachments[key]\n }\n });\n }\n}\n\nreturn output;" }, "position": [ 1328, 1008 ] }, { "id": "34acf446-4393-46e4-9784-f0ed59e3c725", "name": "✨ CV Analyzer Chain", "type": "llm", "params": { "text": "=JOB POSITION APPLIED FOR: {{ $json.position }}\nAPPLICATION DATE: {{ $json.applicationDate }}\nCANDIDATE NAME: {{ $json.candidateName }}\n\nCV TEXT:\n{{ $json.cvText }}\n\nAnalyze the CV and return a structured JSON according to the provided schema.", "prompt": "=JOB POSITION APPLIED FOR: {{ $json.position }}\nAPPLICATION DATE: {{ $json.applicationDate }}\nCANDIDATE NAME: {{ $json.candidateName }}\n\nCV TEXT:\n{{ $json.cvText }}\n\nAnalyze the CV and return a structured JSON according to the provided schema.", "batching": {}, "messages": { "messageValues": [ { "message": "You are a senior recruiter specializing in CV evaluation. Your task is to analyze the provided CV and produce a structured, objective, and detailed assessment.\n\nScoring rules:\n- 0-30: profile not aligned, missing key experience/skills\n- 31-60: partially aligned profile, needs review\n- 61-80: good profile, candidate for interview\n- 81-100: excellent profile, strong hire\n\nThe recommendation must be consistent with the score:\n- REJECT (0-30), REVIEW (31-60), INTERVIEW (61-80), STRONG_HIRE (81-100)\n\nBe rigorous but fair. Always explain the reasoning behind the score." } ] }, "provider": "openai", "promptType": "define", "approximated": true, "hasOutputParser": true }, "position": [ 2368, 1008 ] }, { "id": "dca5260c-583a-4f24-ac9c-8e0115ce5a7e", "name": "Structured Output Parser", "type": "passthrough", "params": { "mode": "noOp", "schemaType": "manual", "inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"nome\": { \"type\": \"string\", \"description\": \"Nome del candidato\" },\n \"cognome\": { \"type\": \"string\", \"description\": \"Cognome del candidato\" },\n \"email\": { \"type\": \"string\", \"description\": \"Email del candidato\" },\n \"telefono\": { \"type\": \"string\", \"description\": \"Numero di telefono\" },\n \"data_candidatura\": { \"type\": \"string\", \"description\": \"Data candidatura YYYY-MM-DD\" },\n \"posizione\": { \"type\": \"string\", \"description\": \"Posizione per cui si candida\" },\n \"anni_esperienza\": { \"type\": \"number\", \"description\": \"Anni di esperienza totale\" },\n \"competenze_chiave\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" },\n \"description\": \"Lista delle competenze tecniche principali\"\n },\n \"lingue\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" },\n \"description\": \"Lingue parlate con livello\"\n },\n \"titolo_studio\": { \"type\": \"string\", \"description\": \"Titolo di studio piu alto\" },\n \"spiegazione_breve\": {\n \"type\": \"string\",\n \"description\": \"Sintesi del profilo in massimo 200 caratteri\"\n },\n \"spiegazione_dettagliata\": {\n \"type\": \"string\",\n \"description\": \"Analisi dettagliata 300-500 parole con punti di forza, gap, fit con la posizione\"\n },\n \"punti_forza\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" },\n \"description\": \"Lista dei principali punti di forza\"\n },\n \"punti_debolezza\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" },\n \"description\": \"Lista delle aree di miglioramento o gap rispetto alla posizione\"\n },\n \"punteggio\": {\n \"type\": \"number\",\n \"minimum\": 0,\n \"maximum\": 100,\n \"description\": \"Punteggio di fit con la posizione da 0 a 100\"\n },\n \"raccomandazione\": {\n \"type\": \"string\",\n \"enum\": [\"REJECT\", \"REVIEW\", \"INTERVIEW\", \"STRONG_HIRE\"],\n \"description\": \"Raccomandazione finale\"\n }\n },\n \"required\": [\n \"nome\",\n \"cognome\",\n \"posizione\",\n \"spiegazione_breve\",\n \"spiegazione_dettagliata\",\n \"punteggio\",\n \"raccomandazione\"\n ]\n}" }, "position": [ 2576, 1248 ] }, { "id": "bb290e42-ed39-4ff0-8bf4-5c4c97469b1f", "name": "✅ Validate & Build Email", "type": "code", "params": { "jsCode": "// ═══════════════════════════════════════════════════\n// VALIDATE & ENRICH + BUILD EMAIL HTML\n// ═══════════════════════════════════════════════════\nconst items = $input.all();\nconst output = [];\n\nfor (const item of items) {\n let parsed = item.json.output || item.json;\n \n // Safety net: handle string responses\n if (typeof parsed === 'string') {\n try {\n parsed = JSON.parse(parsed.replace(/```json\\s*/g, '').replace(/```\\s*/g, '').trim());\n } catch (err) {\n output.push({\n json: {\n error: true,\n errorMessage: 'Parse error: ' + err.message,\n rawResponse: item.json\n }\n });\n continue;\n }\n }\n \n // Validate required fields\n const requiredFields = ['nome', 'cognome', 'posizione', 'punteggio', 'raccomandazione'];\n const missing = requiredFields.filter(f => !(f in parsed));\n if (missing.length > 0) {\n output.push({\n json: {\n error: true,\n errorMessage: 'Missing fields: ' + missing.join(', '),\n partialData: parsed\n }\n });\n continue;\n }\n \n // Retrieve upstream context\n const ctx = $node['🧹 Clean Text'].json;\n const meta = ctx._meta || {};\n \n // Clamp score to [0, 100]\n parsed.punteggio = Math.max(0, Math.min(100, Number(parsed.punteggio) || 0));\n const score = parsed.punteggio;\n \n // Force score <-> recommendation consistency\n const expectedRec = score <= 30 ? 'REJECT'\n : score <= 60 ? 'REVIEW'\n : score <= 80 ? 'INTERVIEW'\n : 'STRONG_HIRE';\n const recCorrected = parsed.raccomandazione !== expectedRec;\n if (recCorrected) {\n parsed.raccomandazione_originale = parsed.raccomandazione;\n parsed.raccomandazione = expectedRec;\n }\n \n // Execution time\n const executionTime = meta.executionStart ? ((Date.now() - meta.executionStart) / 1000).toFixed(1) : 'N/A';\n \n // Score badge color\n const scoreColor = score >= 81 ? '#22c55e'\n : score >= 61 ? '#3b82f6'\n : score >= 31 ? '#f59e0b'\n : '#ef4444';\n \n // Build HTML email\n const puntiForza = (parsed.punti_forza || []).map(p => `

${p}

`).join('');\n const puntiDebolezza = (parsed.punti_debolezza || []).map(p => `

${p}

`).join('');\n const competenze = (parsed.competenze_chiave || []).map(c => `${c}`).join(' ');\n const lingue = (parsed.lingue || []).join(' · ');\n \n const emailHtml = `\n

🎯 New top candidate

${parsed.nome} ${parsed.cognome}

${parsed.posizione}

\n \n

Score

${score}/100

Recommendation

${parsed.raccomandazione}

Years of experience

${parsed.anni_esperienza || 'N/A'}

\n \n

\n Summary: ${parsed.spiegazione_breve}\n

\n \n

📋 Profile

\n \n \n \n \n \n

Email	${parsed.email \|\| 'N/A'}
Phone	${parsed.telefono \|\| 'N/A'}
Education	${parsed.titolo_studio \|\| 'N/A'}
Languages	${lingue \|\| 'N/A'}

\n \n

🛠 Key Skills

${competenze}

\n \n

✓ Strengths

${puntiForza}\n

⚠ Weaknesses

${puntiDebolezza}\n

\n \n

📝 Detailed Analysis

${parsed.spiegazione_dettagliata}

\n \n ${recCorrected ? `

⚠️ Recommendation auto-corrected from \"${parsed.raccomandazione_originale}\" a \"${parsed.raccomandazione}\" per coerenza con il punteggio.

` : ''}\n \n

⏱ ${executionTime}s

📄 Open CV on Drive

🤖 Llama 3.3 70B (Groq)

\n `;\n \n output.push({\n json: {\n ...parsed,\n _emailHtml: emailHtml,\n _emailSubject: `🎯 ${parsed.nome} ${parsed.cognome} - Score ${score}/100 (${parsed.raccomandazione})`,\n cv_drive_link: ctx.driveLink,\n cv_filename: ctx.fileName,\n processed_at: new Date().toISOString(),\n execution_time: executionTime,\n error: false\n }\n });\n}\n\nreturn output;" }, "position": [ 2848, 1008 ] }, { "id": "093a5c93-4f3a-4572-b6a6-e4a1918584fc", "name": "Has Error?", "type": "if", "params": { "options": {}, "conditions": { "options": { "version": 1, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "error-check", "operator": { "type": "boolean", "operation": "equals" }, "leftValue": "={{ $json.error }}", "rightValue": true } ] } }, "position": [ 3152, 1008 ] }, { "id": "8c1f4352-064f-420e-8b24-68c4a127fea1", "name": "Score >= 75?", "type": "if", "params": { "options": {}, "conditions": { "options": { "version": 1, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "score-threshold", "operator": { "type": "number", "operation": "gte" }, "leftValue": "={{ $json.punteggio }}", "rightValue": 75 } ] } }, "position": [ 3728, 1104 ] }, { "id": "1b31fddc-ba98-462c-b85e-e67440441926", "name": "📧 Notify Recruiter", "type": "integration", "params": { "html": "={{ $json._emailHtml }}", "options": {}, "service": "smtp", "subject": "={{ $json._emailSubject }}", "toEmail": "user@example.com", "fromEmail": "user@example.com", "operation": "read" }, "position": [ 4048, 992 ] }, { "id": "364cbfe9-aedc-4bae-b67f-26f371aa86a0", "name": "⚠️ Notify Error", "type": "integration", "params": { "options": {}, "service": "smtp", "subject": "❌ CV Rating Pipeline Error", "toEmail": "user@example.com", "fromEmail": "user@example.com", "operation": "read" }, "position": [ 3600, 864 ] }, { "id": "8a1e7307-e39c-4830-9b27-45a857d79598", "name": "Share file", "type": "integration", "params": { "fileId": { "__rl": true, "mode": "id", "value": "={{ $json.id }}" }, "options": {}, "service": "googleDrive", "operation": "share", "permissionsUi": { "permissionsValues": { "role": "reader", "type": "anyone" } } }, "position": [ 1696, 1008 ] }, { "id": "e74acfd0-5f82-4ffa-840d-113b9d6e3c52", "name": "📁 Upload Drive", "type": "integration", "params": { "name": "={{ $json.fileName }}", "driveId": { "__rl": true, "mode": "list", "value": "", "cachedResultUrl": "", "cachedResultName": "" }, "options": {}, "service": "googleDrive", "folderId": { "__rl": true, "mode": "id", "value": "", "cachedResultUrl": "", "cachedResultName": "" }, "operation": "read", "inputDataFieldName": "cv" }, "position": [ 1536, 1008 ] }, { "id": "0b9ce595-7d22-46c9-80b9-cec8f930a152", "name": "🧠 Mistral OCR", "type": "http", "params": { "url": "https://api.mistral.ai/v1/ocr", "method": "POST", "options": { "timeout": 60000 }, "jsonBody": "={\n \"model\": \"mistral-ocr-latest\",\n \"document\": {\n \"type\": \"document_url\",\n \"document_url\": \"https://drive.google.com/uc?export=download&id={{ $node['📁 Upload Drive'].json.id }}\"\n },\n \"include_image_base64\": false\n}", "sendBody": true, "sendHeaders": true, "specifyBody": "json", "authentication": "predefinedCredentialType", "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] }, "nodeCredentialType": "mistralCloudApi" }, "position": [ 1936, 1008 ] }, { "id": "1e3d73b1-f241-49da-be52-8b44d3e54f1a", "name": "Groq Chat Model", "type": "llm", "params": { "model": "llama-3.3-70b-versatile", "options": { "temperature": 0.2, "maxTokensToSample": 2000 }, "provider": "openai", "temperature": 0.2 }, "position": [ 2320, 1248 ] }, { "id": "98f7dfd0-d690-4fdc-9ddd-ef3e15fc3bdb", "name": "Append row in sheet", "type": "integration", "params": { "service": "googleSheets", "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "", "cachedResultUrl": "", "cachedResultName": "" }, "documentId": { "__rl": true, "mode": "list", "value": "", "cachedResultUrl": "", "cachedResultName": "" } }, "position": [ 3488, 1120 ] }, { "id": "36269d3c-8615-4cc9-b84e-146f89a92ddb", "name": "CV check", "type": "if", "params": { "options": {}, "conditions": { "options": { "version": 1, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "error-check", "operator": { "type": "string", "operation": "contains" }, "leftValue": "={{ $json.subject }}", "rightValue": "ADD_HEADER_INDEED_MAIL" } ] } }, "position": [ 1168, 1104 ] }, { "id": "a5720f62-a4e6-4737-a4c8-e2ae8b914b4a", "name": "🧹 Clean Text", "type": "code", "params": { "jsCode": "// ═══════════════════════════════════════════════════\n// CLEAN & NORMALIZE OCR OUTPUT\n// ═══════════════════════════════════════════════════\nconst items = $input.all();\nconst output = [];\n\nfor (const item of items) {\n const ocrResponse = item.json;\n let fullText = '';\n \n if (ocrResponse.pages && Array.isArray(ocrResponse.pages)) {\n fullText = ocrResponse.pages\n .map(p => p.markdown || p.text || '')\n .join('\\n\\n');\n }\n \n // Normalize whitespace and newlines\n fullText = fullText\n .replace(/\\s{3,}/g, ' ')\n .replace(/\\n{3,}/g, '\\n\\n')\n .trim();\n \n // Retrieve context from previous nodes (production workflow)\n const meta = $('Extract Email Metadata').first().json;\n const drive = $('📁 Upload Drive').first().json;\n \n output.push({\n json: {\n _meta: meta._meta,\n cvText: fullText,\n candidateName: meta.candidateName,\n position: meta.position,\n applicationDate: meta.date,\n fileName: meta.fileName,\n driveLink: drive.webViewLink,\n driveId: drive.id,\n textLength: fullText.length\n }\n });\n}\n\n// Drop binary data to keep the flow lightweight\nreturn output.map(item => ({ json: item.json }));" }, "position": [ 2128, 1008 ] } ] }

Score and triage Indeed CVs with Mistral OCR, Groq, and Google Sheets