{
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        "httpMethod": "POST",
        "path": "seguimiento-impuestos-bamboohr-contacto",
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      "name": "Webhook - Buscar contacto BambooHR",
      "webhookId": "seguimiento-impuestos-bamboohr-contacto"
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      "id": "ec0dfdd1-8163-427b-af60-560a00011b9d",
      "name": "Validar solicitud"
    },
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      "parameters": {
        "conditions": {
          "options": {
            "caseSensitive": true,
            "leftValue": "",
            "typeValidation": "strict",
            "version": 2
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          "conditions": [
            {
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              "leftValue": "={{ $json.valid }}",
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                "operation": "true",
                "singleValue": true
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      "id": "967fe0fe-9857-44c6-a61f-76960961bbab",
      "name": "Solicitud válida"
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://glm.bamboohr.com/api/v1/reports/custom?format=JSON&onlyCurrent=false",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpBasicAuth",
        "sendHeaders": true,
        "headerParameters": {
          "parameters": [
            {
              "name": "Accept",
              "value": "application/json"
            }
          ]
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": {
          "title": "Información completa de empleados BambooHR - Seguimiento de Impuestos",
          "fields": [
            "firstName",
            "middleName",
            "lastName",
            "displayName",
            "department",
            "division",
            "location",
            "customPosicion-Cliente",
            "hireDate",
            "originalHireDate",
            "status",
            "employeeNumber",
            "workEmail",
            "terminationDate",
            "supervisor",
            "startDate",
            "jobTitle",
            "employmentStatus",
            "email",
            "country",
            "city",
            "address1"
          ]
        },
        "options": {
          "response": {
            "response": {
              "responseFormat": "json"
            }
          },
          "timeout": 300000
        }
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      "id": "e6a5c8a8-25b4-48dd-96e7-02e68912ca6a",
      "name": "Generar reporte completo BambooHR",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.4,
      "position": [
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      ],
      "retryOnFail": true,
      "maxTries": 3,
      "waitBetweenTries": 2000,
      "credentials": {
        "httpBasicAuth": {
          "id": "7VrpNZ2jBLmiJ35q",
          "name": "BambooHR GLM Full Access"
        }
      }
    },
    {
      "parameters": {
        "jsCode": "const query = String($('Validar solicitud').item.json.full_name ?? '').trim();\nconst response = $json ?? {};\nconst employees = Array.isArray(response.employees)\n  ? response.employees\n  : Array.isArray(response.data)\n    ? response.data\n    : Array.isArray(response)\n      ? response\n      : [];\n\nconst normalize = (value) => String(value ?? '')\n  .normalize('NFD')\n  .replace(/[\\u0300-\\u036f]/g, '')\n  .toLowerCase()\n  .replace(/[^a-z0-9\\s]/g, ' ')\n  .replace(/\\s+/g, ' ')\n  .trim();\n\nconst tokens = (value) => normalize(value).split(' ').filter((token) => token.length > 1);\n\nconst levenshtein = (a, b) => {\n  if (!a) return b.length;\n  if (!b) return a.length;\n  const previous = Array.from({ length: b.length + 1 }, (_, index) => index);\n  for (let i = 1; i <= a.length; i += 1) {\n    let diagonal = previous[0];\n    previous[0] = i;\n    for (let j = 1; j <= b.length; j += 1) {\n      const old = previous[j];\n      const cost = a[i - 1] === b[j - 1] ? 0 : 1;\n      previous[j] = Math.min(previous[j] + 1, previous[j - 1] + 1, diagonal + cost);\n      diagonal = old;\n    }\n  }\n  return previous[b.length];\n};\n\nconst similarity = (a, b) => {\n  const longest = Math.max(a.length, b.length, 1);\n  return 1 - levenshtein(a, b) / longest;\n};\n\nconst tokenF1 = (aTokens, bTokens) => {\n  if (!aTokens.length || !bTokens.length) return 0;\n  const a = new Set(aTokens);\n  const b = new Set(bTokens);\n  const common = [...a].filter((token) => b.has(token)).length;\n  if (!common) return 0;\n  const precision = common / b.size;\n  const recall = common / a.size;\n  return (2 * precision * recall) / (precision + recall);\n};\n\nconst countryAliases = [\n  { code: 'DO', name: 'República Dominicana', aliases: ['dominican republic', 'republica dominicana', 'santo domingo', 'dominicana', 'rep dom'] },\n  { code: 'PR', name: 'Puerto Rico', aliases: ['puerto rico'] },\n  { code: 'JM', name: 'Jamaica', aliases: ['jamaica'] },\n  { code: 'TT', name: 'Trinidad y Tobago', aliases: ['trinidad and tobago', 'trinidad & tobago', 'trinidad y tobago', 'trinidad', 'tobago'] },\n  { code: 'SV', name: 'El Salvador', aliases: ['el salvador', 'salvador'] },\n  { code: 'GT', name: 'Guatemala', aliases: ['guatemala'] },\n  { code: 'HN', name: 'Honduras', aliases: ['honduras'] },\n  { code: 'CR', name: 'Costa Rica', aliases: ['costa rica'] },\n  { code: 'CO', name: 'Colombia', aliases: ['colombia'] },\n  { code: 'MX', name: 'México', aliases: ['mexico', 'méxico'] },\n  { code: 'NI', name: 'Nicaragua', aliases: ['nicaragua'] },\n  { code: 'PA', name: 'Panamá', aliases: ['panama', 'panamá'] },\n];\n\nconst resolveCountry = (employee) => {\n  const haystack = normalize([\n    employee.country,\n    employee.location,\n    employee.city,\n    employee.division,\n    employee.department,\n    employee.address1,\n  ].filter(Boolean).join(' '));\n\n  if (/\\bregional\\b|\\bregion\\b/.test(haystack)) {\n    return { code: 'REG', name: 'Regional' };\n  }\n\n  for (const country of countryAliases) {\n    if (country.aliases.some((alias) => haystack.includes(normalize(alias)))) {\n      return { code: country.code, name: country.name };\n    }\n  }\n\n  return { code: 'REG', name: 'Regional' };\n};\n\nconst resolveArea = (employee) => {\n  const text = normalize([\n    employee.department,\n    employee.division,\n    employee.jobTitle,\n    employee['customPosicion-Cliente'],\n  ].filter(Boolean).join(' '));\n\n  if (/nomina|payroll|compensacion|compensation|beneficios|benefits/.test(text)) return 'nomina';\n  if (/administracion|administrativo|administrative|finance|finanzas|contabilidad|accounting|impuesto|tax|tesoreria|treasury|conciliacion|compras|procurement/.test(text)) return 'admin';\n  return 'other';\n};\n\n\nconst queryNormalized = normalize(query);\nconst queryTokens = tokens(query);\nconst candidates = [];\n\nfor (const employee of employees) {\n  const constructedName = [employee.firstName, employee.middleName, employee.lastName]\n    .filter(Boolean)\n    .join(' ')\n    .replace(/\\s+/g, ' ')\n    .trim();\n  const displayName = String(employee.displayName ?? '').trim();\n  const fullName = displayName || constructedName;\n  if (!fullName) continue;\n\n  const nameVariants = [...new Set([fullName, constructedName, displayName].filter(Boolean))];\n  let score = 0;\n  for (const variant of nameVariants) {\n    const normalizedVariant = normalize(variant);\n    const variantTokens = tokens(variant);\n    let current = 0;\n    if (normalizedVariant === queryNormalized) current = 100;\n    else if (normalizedVariant.startsWith(queryNormalized)) current = 91;\n    else if (normalizedVariant.includes(queryNormalized)) current = 85;\n    else if (queryNormalized.includes(normalizedVariant)) current = 78;\n\n    const f1 = tokenF1(queryTokens, variantTokens);\n    const editSimilarity = similarity(queryNormalized, normalizedVariant);\n    current = Math.max(current, f1 * 82, editSimilarity * 76);\n    if (queryTokens.every((token) => variantTokens.includes(token))) current += 8;\n    score = Math.max(score, current);\n  }\n\n  const status = String(employee.status ?? employee.employmentStatus ?? '').trim();\n  if (/active|activo/i.test(status)) score += 3;\n  if (score < 45) continue;\n\n  const country = resolveCountry(employee);\n  const email = String(employee.workEmail || employee.email || '').trim().toLowerCase();\n\n  candidates.push({\n    id: String(employee.id ?? employee.employeeId ?? employee.employeeNumber ?? fullName),\n    employeeNumber: String(employee.employeeNumber ?? ''),\n    fullName,\n    displayName: displayName || fullName,\n    email,\n    jobTitle: String(employee.jobTitle ?? employee['customPosicion-Cliente'] ?? '').trim(),\n    department: String(employee.department ?? '').trim(),\n    division: String(employee.division ?? '').trim(),\n    location: String(employee.location ?? employee.city ?? '').trim(),\n    countryCode: country.code,\n    countryName: country.name,\n    area: resolveArea(employee),\n    status,\n    score: Math.min(100, Math.round(score)),\n    matchQuality: score >= 95 ? 'exacta' : score >= 72 ? 'alta' : 'media',\n  });\n}\n\nconst unique = new Map();\nfor (const candidate of candidates.sort((a, b) => {\n  const activeA = /active|activo/i.test(a.status) ? 1 : 0;\n  const activeB = /active|activo/i.test(b.status) ? 1 : 0;\n  return b.score - a.score || activeB - activeA || a.fullName.localeCompare(b.fullName);\n})) {\n  const key = candidate.id || candidate.email || normalize(candidate.fullName);\n  if (!unique.has(key)) unique.set(key, candidate);\n}\n\nreturn [{\n  json: {\n    ok: true,\n    query,\n    count: Math.min(unique.size, 8),\n    candidates: [...unique.values()].slice(0, 8),\n  },\n}];"
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      ],
      "id": "3edf99bc-ae3c-4473-a6cb-dd83e494f6cc",
      "name": "Buscar coincidencias robustas"
    },
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        "respondWith": "json",
        "responseBody": "={{ $json }}",
        "options": {
          "responseCode": 200,
          "responseHeaders": {
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              {
                "name": "Access-Control-Allow-Origin",
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    },
    {
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        "respondWith": "json",
        "responseBody": "={{ { ok: false, message: $json.message, candidates: [] } }}",
        "options": {
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    "timezone": "America/Santo_Domingo",
    "callerPolicy": "workflowsFromSameOwner"
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}