Automatisation du tri des CV et de la vérification des candidats avec l'IA et l'analyse d'e-mails

• •Aucun prérequis spécial, prêt à l'emploi après importation

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        "jsCode": "// Access the extracted PDF text\nconst fileContent = ($input.first().json.text || '').toLowerCase();\nconst keywordsToDepartments = {\n  hr: 'HR',\n  bde: 'BDE',\n  'business development': 'BDE',\n  seo: 'SEO',\n  devops: 'DevOps',\n  developer: 'Development',\n  engineer: 'Engineering',\n  marketing: 'Marketing',\n  sales: 'Sales',\n  support: 'Support',\n  tester: 'QA',\n  qa: 'QA',\n};\n\n// Define a priority order (higher number = higher priority)\nconst priority = {\n  devops: 3,\n  developer: 3,\n  engineer: 3,\n  seo: 2,\n  bde: 2,\n  'business development': 2,\n  marketing: 2,\n  sales: 2,\n  support: 2,\n  tester: 2,\n  qa: 2,\n  hr: 1,\n};\n\n// Find all matching departments with their priorities\nlet matches = [];\nfor (const [keyword, department] of Object.entries(keywordsToDepartments)) {\n  if (fileContent.includes(keyword)) {\n    matches.push({ department, priority: priority[keyword] || 0 });\n  }\n}\n\n// Extract the username (first line of the CV text)\nconst originalText = $input.first().json.text || '';\nconst username = originalText.split('\\n')[0].trim(); // First line, e.g., \"Komal Shah\"\n\n// If matches are found, return the department with the highest priority along with the username\nif (matches.length > 0) {\n  const bestMatch = matches.reduce((best, current) =>\n    current.priority > best.priority ? current : best\n  );\n  return [{ department: bestMatch.department, username }];\n}\n\nreturn [{ department: 'Unknown', username }];"
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      "name": "Notifier les RH d'un CV non valide",
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      "parameters": {
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        "subject": "CV Processing Error",
        "toEmail": "abc@gmail.com",
        "fromEmail": "xyz@gmail.com"
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