Webhook | Resumen de artículo

Intermedio

Este es unAIflujo de automatización del dominio deautomatización que contiene 12 nodos.Utiliza principalmente nodos como Set, Html, Webhook, SplitOut, Aggregate, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Resumir papers de Arxiv con ChatGPT

Requisitos previos
  • Punto final de HTTP Webhook (n8n generará automáticamente)
  • Pueden requerirse credenciales de autenticación para la API de destino
  • 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
{
  "id": "5IAbyLhZX99QS1ff",
  "meta": {
    "instanceId": "0b0f5302e78710cf1b1457ee15a129d8e5d83d4e366bd96d14cc37da6693e692"
  },
  "name": "Webhook | Paper Summarization",
  "tags": [],
  "nodes": [
    {
      "id": "cf2bfb6d-c5ae-46e8-9382-274f37129291",
      "name": "Cadena de Resumen",
      "type": "@n8n/n8n-nodes-langchain.chainSummarization",
      "position": [
        1000,
        0
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 2
    },
    {
      "id": "b1ab5c2c-f7df-4f2b-bf2d-e3f11a76b691",
      "name": "Modelo de Chat OpenAI",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1000,
        140
      ],
      "parameters": {
        "model": "gpt-3.5-turbo",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "kfEFSW14uz5PPu9A",
          "name": "OpenAi account(n8n_)"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "da17d97e-218a-466d-b356-ccdb63120626",
      "name": "Solicitud a Página del Artículo",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        340,
        0
      ],
      "parameters": {
        "url": "=https://arxiv.org/html/{{ $json.query.id }}",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "034a05a8-78ef-4037-a41d-e2ae7e747378",
      "name": "Extraer Contenidos",
      "type": "n8n-nodes-base.html",
      "position": [
        500,
        0
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "abstract",
              "cssSelector": "div.ltx_abstract"
            },
            {
              "key": "sections",
              "cssSelector": "div.ltx_para",
              "returnArray": true
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "88cae164-4e9c-40ab-bbd7-b070863d222d",
      "name": "Dividir Todas las Secciones",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        660,
        0
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "sections"
      },
      "typeVersion": 1
    },
    {
      "id": "047ca863-0ffc-40e2-ac1e-57cdea011063",
      "name": "Eliminar enlaces inútiles",
      "type": "n8n-nodes-base.set",
      "position": [
        840,
        0
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "4a821a88-9adc-4f9e-8a29-25b03bf7f5a3",
              "name": "sections",
              "type": "string",
              "value": "={{ $json.sections.replaceAll(/\\[.*?\\]/g, '')}}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "3ccb4f31-fd75-4eac-be93-08b22c48ea7f",
      "name": "Agregar contenido resumido",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        1300,
        0
      ],
      "parameters": {
        "options": {},
        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "response.text"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "f836d2c0-a28c-4704-a2cc-ec13e3dabfd7",
      "name": "Reorganizar Resumen del Artículo",
      "type": "@n8n/n8n-nodes-langchain.openAi",
      "position": [
        1440,
        0
      ],
      "parameters": {
        "modelId": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-3.5-turbo",
          "cachedResultName": "GPT-3.5-TURBO"
        },
        "options": {},
        "messages": {
          "values": [
            {
              "role": "system",
              "content": "=Based on the provided research paper text, generate a summary divided into the following four sections. Each section must include the required details listed below:\n\nAbstract Overview:\n\nSummarize the research topic, objectives, and methodology.\nHighlight the main results and conclusions.\nConvey the overall core message of the paper.\nIntroduction:\n\nOutline the background and motivation behind the research.\nDiscuss existing literature, emphasizing differences or gaps.\nClearly state the necessity and objectives of the study.\nResults:\n\nPresent the key experimental results and data analysis.\nHighlight significant findings, including any important figures or data points if applicable.\nProvide a brief interpretation of the results.\nConclusion:\n\nSummarize the implications and significance of the findings.\nMention any limitations of the study.\nOffer suggestions for future research and state the final conclusions.\nEnsure that each section includes all critical details while avoiding unnecessary elaboration. The summary should flow logically from one section to the next, reflecting the overall structure and content of the original paper."
            },
            {
              "content": "={{ $json.text.join('|') }}"
            }
          ]
        },
        "simplify": false
      },
      "credentials": {
        "openAiApi": {
          "id": "kfEFSW14uz5PPu9A",
          "name": "OpenAi account(n8n_)"
        }
      },
      "typeVersion": 1.7
    },
    {
      "id": "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8",
      "name": "Extractor de Contenido",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        1740,
        0
      ],
      "parameters": {
        "text": "={{ $json.choices[0].message.content }}",
        "options": {},
        "attributes": {
          "attributes": [
            {
              "name": "Abstract Overview",
              "required": true,
              "description": "the abstract overview in short"
            },
            {
              "name": "Introduction",
              "required": true,
              "description": "Describe the context, motivation, and problem statement, indeed."
            },
            {
              "name": "Results",
              "required": true,
              "description": "Outline the main results or findings of the study, indeed."
            },
            {
              "name": "Conclusion",
              "required": true,
              "description": "Conclude with the overall achievements and contributions of the paper, indeed."
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "71e4f88d-a13f-4d1e-a6af-73c3570dc1b7",
      "name": "Modelo de Chat OpenAI1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1920,
        140
      ],
      "parameters": {
        "model": "gpt-3.5-turbo",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "kfEFSW14uz5PPu9A",
          "name": "OpenAi account(n8n_)"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "b82b133e-b2e5-4ed6-9157-f0b4cdd3e4d3",
      "name": "Webhook",
      "type": "n8n-nodes-base.webhook",
      "position": [
        140,
        0
      ],
      "webhookId": "b6362ca0-c954-45ce-8997-7f18d8d9f8a4",
      "parameters": {
        "path": "paper-summarization",
        "options": {},
        "responseMode": "responseNode"
      },
      "typeVersion": 2
    },
    {
      "id": "1789c207-0d0d-4aaa-a6a7-0185972ce8ad",
      "name": "Responder a Webhook",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        2060,
        0
      ],
      "parameters": {
        "options": {},
        "respondWith": "json",
        "responseBody": "={{ $json.output }}"
      },
      "typeVersion": 1.1
    }
  ],
  "active": true,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "04055cba-004d-47ed-8a08-c1c3bb47debd",
  "connections": {
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    },
    "034a05a8-78ef-4037-a41d-e2ae7e747378": {
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    "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8": {
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    "b1ab5c2c-f7df-4f2b-bf2d-e3f11a76b691": {
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    "da17d97e-218a-466d-b356-ccdb63120626": {
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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?

Intermedio - 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
Intermedio
Número de nodos12
Categoría1
Tipos de nodos11
Descripción de la dificultad

Adecuado para usuarios con experiencia intermedia, flujos de trabajo de complejidad media con 6-15 nodos

Autor

12 years in development, South Korea, Seoul

Enlaces externos
Ver en n8n.io

Compartir este flujo de trabajo

Categorías

Categorías: 34