Automatización del envío de formularios de pedido de compra desde archivos adjuntos de Excel en Outlook con IA

Avanzado

Este es unAIflujo de automatización del dominio deautomatización que contiene 22 nodos.Utiliza principalmente nodos como If, Set, Code, ExtractFromFile, MicrosoftOutlook, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Automatizar el envío de formularios de orden de compra desde adjuntos de Excel de Outlook con IA

Requisitos previos
  • Clave de API de OpenAI
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
{
  "meta": {
    "instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "b87cc222-82ec-4b46-9573-68f41d096969",
      "name": "Nota Adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        640,
        620
      ],
      "parameters": {
        "color": 7,
        "width": 740,
        "height": 680,
        "content": "## 2. Manually Convert XLSX to Markdown\n[Learn more about the Extract From File node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.extractfromfile/)\n\nToday's LLMs cannot parse Excel files directly so the best we can do is to convert the spreadsheet into a format that they can, namely markdown. This conversion is also a good solution for excels which aren't really datasheets - the cells are used like layout elements - which is still common for invoices and purchase orders.\n\nTo perform the conversion, we can use the 'Extract from File' node to get the each row from the xlsx and then iterate and concatenate to form our markdown table using the code node."
      },
      "typeVersion": 1
    },
    {
      "id": "c4c55042-02c8-4364-ae7e-d1ec5a75437a",
      "name": "Nota Adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1400,
        620
      ],
      "parameters": {
        "color": 7,
        "width": 640,
        "height": 680,
        "content": "## 3. Extract Purchase Order Details using AI\n[Learn more about the Information Extractor](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor)\n\nData entry is probably the number one reason as to why we need AI/LLMs. This time consuming and menial task can be completed in seconds and with a high degree of accuracy. Here, we ask the AI to extract each event with the term dates to a list of events using structured output."
      },
      "typeVersion": 1
    },
    {
      "id": "b9530f93-464b-4116-add7-da218fe8eb12",
      "name": "Nota Adhesiva5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -700,
        -80
      ],
      "parameters": {
        "width": 460,
        "height": 1400,
        "content": "## Try it out!\n### This n8n template imports purchase order submissions from Outlook and converts attached purchase order form in XLSX format into structured output.\n\nData entry jobs with user-submitted XLSX forms is a time consuming, incredibly mundane but necessary tasks which in likelihood are inherited and critical to business operation.\n\nWhile we could dream of system overhauls and modernisation, the fact is that change is hard. There is another way however -  using n8n and AI!\n\n### How it works\n* An Outlook trigger is used to watch for incoming purchase order forms submitted via a shared inbox.\n* The email attachment for the submission is a form in xlsx format - like this one https://1drv.ms/x/c/8f1f7dda12b7a145/ETWH8dKwgZ1OiVz7ISUWYf8BwiyihBjXPXEbCYkVi8XDyw?e=WWU2eR - which is imported into the workflow.\n* The 'Extract from File' node is used with the 'code' node to convert the xlsx file to markdown. This is so our LLM can understand it.\n* The Information Extractor node is used to read and extract the relevant purchase order details and line items from the form.\n* A simple validation step is used to check for common errors such as missing PO number or the amounts not matching up. A notification is automated to reply to the buyer if so.\n* Once validation passes, a confirmation is sent to the buyer and the purchase order structured output can be sent along to internal systems.\n\n### How to use\n* This template only works if you're expecting and receiving forms in XLSX format. These can be invoices, request forms as well as purchase order forms.\n* Update the Outlook nodes with your email or other emails as required.\n* What's next? I've omitted the last steps to send to an ERP or accounting system as this is dependent on your org.\n\n### Requirements\n* Outlook for Emails\n  * Check out how to setup credentials here: https://docs.n8n.io/integrations/builtin/credentials/microsoft/\n* OpenAI for LLM document understanding and extraction.\n\n### Customising the workflow\n* This template should work for other Excel files. Some will be more complicated than others so experiment with different parsers and extraction tools and strategies.\n* Customise the Information Extractor Schema to pull out the specific data you need. For example, capture any notes or comments given by the buyer.\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
      },
      "typeVersion": 1
    },
    {
      "id": "f5a2d1e7-f73b-4bfa-8e02-f30db275bbcc",
      "name": "Extraer Detalles de la Orden de Compra",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        1500,
        920
      ],
      "parameters": {
        "text": "={{ $json.table }}",
        "options": {
          "systemPromptTemplate": "Capture the values as seen. Do not convert dates."
        },
        "schemaType": "manual",
        "inputSchema": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"purchase_order_number\": { \"type\": \"string\" },\n    \"purchase_order_date\": { \"type\": \"string\" },\n    \"purchase_order_total\": { \"type\": \"number\" },\n    \"vendor_name\": { \"type\": \"string\" },\n    \"vendor_address\": { \"type\": \"string\" },\n    \"vendor_contact\": { \"type\": \"string\" },\n    \"delivery_contact\": { \"type\": \"string\" },\n    \"delivery_address\": { \"type\": \"string\" },\n    \"delivery_method\": { \"type\": \"string\" },\n    \"items\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"description\": { \"type\": \"string\" },\n          \"part_number\": { \"type\": \"string\" },\n          \"quantity\": { \"type\": \"number\" },\n          \"unit\": { \"type\": \"number\" },\n          \"unit_price\": { \"type\": \"number\" }\n        }\n      }\n    }\n  }\n}"
      },
      "typeVersion": 1
    },
    {
      "id": "0ce545f0-8147-4ad2-bb9e-14ef0b0c26ef",
      "name": "¿Es Documento de Excel?",
      "type": "n8n-nodes-base.if",
      "position": [
        760,
        1020
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "f723ab0a-8f2d-4501-8273-fd6455c57cdd",
              "operator": {
                "name": "filter.operator.equals",
                "type": "string",
                "operation": "equals"
              },
              "leftValue": "={{ $binary.data.mimeType }}",
              "rightValue": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "ccbd9531-66be-4e07-8b73-faf996622f9f",
      "name": "Nota Adhesiva7",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -220,
        460
      ],
      "parameters": {
        "color": 5,
        "width": 340,
        "height": 140,
        "content": "### PURCHASE ORDER EXAMPLE\nThis is the purchase order XLSX which is used an example for this template.\nhttps://1drv.ms/x/c/8f1f7dda12b7a145/ETWH8dKwgZ1OiVz7ISUWYf8BwiyihBjXPXEbCYkVi8XDyw?e=WWU2eR"
      },
      "typeVersion": 1
    },
    {
      "id": "ef8b00eb-dba6-47dd-a825-1aa5c85ee215",
      "name": "Ejecutar Verificaciones",
      "type": "n8n-nodes-base.set",
      "position": [
        2160,
        940
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "049c7aca-7663-4eed-93b4-9eec3760c058",
              "name": "has_po_number",
              "type": "boolean",
              "value": "={{ Boolean($json.output.purchase_order_number) }}"
            },
            {
              "id": "94d2224a-cf81-4a42-acd0-de5276a5e493",
              "name": "has_valid_po_date",
              "type": "boolean",
              "value": "={{ $json.output.purchase_order_date.toDateTime() < $now.plus({ 'day': 1 }) }}"
            },
            {
              "id": "a8f69605-dad6-4ec2-a22f-d13ff99e27cd",
              "name": "has_items",
              "type": "boolean",
              "value": "={{ $json.output.items.length > 0 }}"
            },
            {
              "id": "c11db99e-9cc2-40b7-b3a5-f3c65f88dc13",
              "name": "is_math_correct",
              "type": "boolean",
              "value": "={{\n$json.output.items.map(item => item.unit_price * item.quantity).sum().round(2) === $json.output.purchase_order_total.round(2) }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "801848cc-558c-4a30-aab5-eb403564b68f",
      "name": "¿Es una Orden de Compra Válida?",
      "type": "n8n-nodes-base.if",
      "position": [
        2360,
        940
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "11fa8087-7809-4bc9-9fbe-32bfd35821a6",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ $json.has_po_number }}",
              "rightValue": ""
            },
            {
              "id": "c45ae85a-e060-4416-aa2c-daf58db8ba0e",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ $json.has_valid_po_date }}",
              "rightValue": ""
            },
            {
              "id": "d0ae9518-2f4b-43fb-87b1-7108a6a75424",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ $json.has_items }}",
              "rightValue": ""
            },
            {
              "id": "eed09f78-ce1a-4e09-8940-febcf7e41078",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ $json.is_math_correct }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "7c7dd7a0-45fe-4549-8341-3b3fd18e1725",
      "name": "Extraer desde Archivo",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        980,
        920
      ],
      "parameters": {
        "options": {
          "rawData": true,
          "headerRow": false,
          "includeEmptyCells": true
        },
        "operation": "xlsx"
      },
      "typeVersion": 1
    },
    {
      "id": "dfb6b00f-fe50-42d6-8597-8fdcb562714b",
      "name": "XLSX a Tabla Markdown",
      "type": "n8n-nodes-base.code",
      "position": [
        1180,
        920
      ],
      "parameters": {
        "jsCode": "const rows = $input.all().map(item => item.json.row);\nconst maxLength = Math.max(...rows.map(row => row.length));\n\nconst table = [\n  '|' + rows[0].join('|') + '|',\n  '|' + Array(maxLength).fill(0).map(_ => '-').join('|') + '|',\n  rows.slice(1, rows.length)\n    .filter(row => row.some(Boolean))\n    .map(row =>\n      '|' + row.join('|') + '|'\n    ).join('\\n')\n].join('\\n')\n\nreturn { table }"
      },
      "typeVersion": 2
    },
    {
      "id": "1a3de516-1d21-4664-b2e3-8c8d6ec90ef2",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1600,
        1080
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "1a29236f-5eaa-4a38-a0a1-6e19abd77d2c",
      "name": "Nota Adhesiva2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2060,
        620
      ],
      "parameters": {
        "color": 7,
        "width": 940,
        "height": 680,
        "content": "## 4. Use Simple Validation to Save Time and Effort\n[Learn more about the Edit Fields node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.set)\n\nWith our extracted output, we can run simple validation checks to save on admin time. Common errors such as missing purchase order numbers or miscalculated cost amounts are easy to detect and a quick response can be given. Once validation passes, it's up to you how you use the extracted output next."
      },
      "typeVersion": 1
    },
    {
      "id": "79a39a03-5f71-4021-bcfd-06edbc285e8a",
      "name": "Responder Formato Inválido",
      "type": "n8n-nodes-base.microsoftOutlook",
      "position": [
        980,
        1120
      ],
      "webhookId": "9464583e-9505-49ec-865e-58aa1ab3c2ed",
      "parameters": {
        "message": "PO rejected due to invalid file format. Please try again with XLSX.",
        "options": {},
        "messageId": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $('Outlook Trigger').first().json.id }}"
        },
        "operation": "reply",
        "additionalFields": {},
        "replyToSenderOnly": true
      },
      "credentials": {
        "microsoftOutlookOAuth2Api": {
          "id": "EWg6sbhPKcM5y3Mr",
          "name": "Microsoft Outlook account"
        }
      },
      "typeVersion": 2
    },
    {
      "id": "ec973438-4d6c-4d2e-8702-1d195f514528",
      "name": "Activador de Outlook",
      "type": "n8n-nodes-base.microsoftOutlookTrigger",
      "position": [
        -120,
        920
      ],
      "parameters": {
        "fields": [
          "body",
          "categories",
          "conversationId",
          "from",
          "hasAttachments",
          "internetMessageId",
          "sender",
          "subject",
          "toRecipients",
          "receivedDateTime",
          "webLink"
        ],
        "output": "fields",
        "filters": {
          "hasAttachments": true,
          "foldersToInclude": []
        },
        "options": {
          "downloadAttachments": true
        },
        "pollTimes": {
          "item": [
            {
              "mode": "everyHour"
            }
          ]
        }
      },
      "credentials": {
        "microsoftOutlookOAuth2Api": {
          "id": "EWg6sbhPKcM5y3Mr",
          "name": "Microsoft Outlook account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "fcb173ce-7dad-497a-9376-9650c2a24a84",
      "name": "Responder Rechazo",
      "type": "n8n-nodes-base.microsoftOutlook",
      "position": [
        2580,
        1040
      ],
      "webhookId": "9464583e-9505-49ec-865e-58aa1ab3c2ed",
      "parameters": {
        "message": "=PO Rejected due to the following errors:\n{{\n[\n  !$json.has_po_number ? '* PO number was not provided' : '',\n  !$json.has_valid_po_date ? '* PO date was missing or invalid' : '',\n  !$json.has_items ? '* No line items detected' : '',\n  !$json.is_math_correct ? '* Line items prices do not match up to PO total' : ''\n]\n  .compact()\n  .join('\\n')\n}}",
        "options": {},
        "messageId": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $('Outlook Trigger').first().json.id }}"
        },
        "operation": "reply",
        "additionalFields": {},
        "replyToSenderOnly": true
      },
      "credentials": {
        "microsoftOutlookOAuth2Api": {
          "id": "EWg6sbhPKcM5y3Mr",
          "name": "Microsoft Outlook account"
        }
      },
      "typeVersion": 2
    },
    {
      "id": "64ced193-6b12-4ee9-b1e2-735040648051",
      "name": "Responder Aceptado",
      "type": "n8n-nodes-base.microsoftOutlook",
      "position": [
        2580,
        820
      ],
      "webhookId": "9464583e-9505-49ec-865e-58aa1ab3c2ed",
      "parameters": {
        "message": "=Thank you for the purchase order.\nThis is an automated reply.",
        "options": {},
        "messageId": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $('Outlook Trigger').first().json.id }}"
        },
        "operation": "reply",
        "additionalFields": {},
        "replyToSenderOnly": true
      },
      "credentials": {
        "microsoftOutlookOAuth2Api": {
          "id": "EWg6sbhPKcM5y3Mr",
          "name": "Microsoft Outlook account"
        }
      },
      "typeVersion": 2
    },
    {
      "id": "7bfe0e44-cd5d-4290-ba2e-0064c95bc4e2",
      "name": "Hacer Algo con la Orden de Compra",
      "type": "n8n-nodes-base.noOp",
      "position": [
        2800,
        940
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "6f517f2f-6072-46a2-8a9d-cca4e958d601",
      "name": "Corregir Fechas de Excel",
      "type": "n8n-nodes-base.set",
      "position": [
        1840,
        920
      ],
      "parameters": {
        "mode": "raw",
        "options": {},
        "jsonOutput": "={{\n{\n  output: {\n    ...$json.output,\n    purchase_order_date: $json.output.purchase_order_date\n      ? new Date((new Date(1900, 0, 1)).getTime() + (Number($json.output.purchase_order_date) - 2) * (24 * 60 * 60 * 1000))\n      : $json.output.purchase_order_date\n  }\n}\n}}"
      },
      "typeVersion": 3.4
    },
    {
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      "name": "Nota Adhesiva3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
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        "height": 680,
        "content": "## 1. Wait For Incoming Purchase Orders\n[Read more about the Outlook trigger](https://docs.n8n.io/integrations/builtin/trigger-nodes/n8n-nodes-base.microsoftoutlooktrigger)\n\nOur template starts by watching for new emails to a shared inbox (eg. \"purchase-orders@example.com\") using the Outlook Trigger node. Our goal is to identify and capture buyer purchase orders so that we can automating validate and use AI to reduce the data entry time and cost at scale.\n\nWe can also use the Text Classifier node to validate intent. This ensures we catch valid submissions are not just queries about purchase-orders or replies."
      },
      "typeVersion": 1
    },
    {
      "id": "bb395dfc-2831-4e57-90c9-62f13f84302e",
      "name": "¿Se está Enviando una Orden de Compra?",
      "type": "@n8n/n8n-nodes-langchain.textClassifier",
      "position": [
        80,
        920
      ],
      "parameters": {
        "options": {
          "fallback": "other"
        },
        "inputText": "=from: {{ $json.from.emailAddress.name }} <{{ $json.from.emailAddress.address }}>\nsubject: {{ $json.subject }}\nmessage:\n{{ $json.body.content }}",
        "categories": {
          "categories": [
            {
              "category": "is_purchase_order",
              "description": "The message's intent is to submit a purchase order"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e52ec2e2-8be5-40ab-b1f8-8d7c0b161e1a",
      "name": "No Hacer Nada",
      "type": "n8n-nodes-base.noOp",
      "position": [
        420,
        1040
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "5ca6be4e-bc33-42d7-91bc-d30f7ccfdd25",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        180,
        1080
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini",
          "cachedResultName": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    }
  ],
  "pinData": {},
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}
Preguntas frecuentes

¿Cómo usar este flujo de trabajo?

Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.

¿En qué escenarios es adecuado este flujo de trabajo?

Avanzado - Inteligencia Artificial

¿Es de pago?

Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.

Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos22
Categoría1
Tipos de nodos11
Descripción de la dificultad

Adecuado para usuarios avanzados, flujos de trabajo complejos con 16+ nodos

Autor
Jimleuk

Jimleuk

@jimleuk

Freelance consultant based in the UK specialising in AI-powered automations. I work with select clients tackling their most challenging projects. For business enquiries, send me an email at hello@jimle.uk LinkedIn: https://www.linkedin.com/in/jimleuk/ X/Twitter: https://x.com/jimle_uk

Enlaces externos
Ver en n8n.io

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Categorías

Categorías: 34