Webhook | Résumé d'article

Intermédiaire

Ceci est unAIworkflow d'automatisation du domainecontenant 12 nœuds.Utilise principalement des nœuds comme Set, Html, Webhook, SplitOut, Aggregate, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Résumer des articles de Arxiv avec ChatGPT

Prérequis
  • Point de terminaison HTTP Webhook (généré automatiquement par n8n)
  • Peut nécessiter les informations d'identification d'authentification de l'API cible
  • Clé API OpenAI
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
  "id": "5IAbyLhZX99QS1ff",
  "meta": {
    "instanceId": "0b0f5302e78710cf1b1457ee15a129d8e5d83d4e366bd96d14cc37da6693e692"
  },
  "name": "Webhook | Paper Summarization",
  "tags": [],
  "nodes": [
    {
      "id": "cf2bfb6d-c5ae-46e8-9382-274f37129291",
      "name": "Chaîne de résumé",
      "type": "@n8n/n8n-nodes-langchain.chainSummarization",
      "position": [
        1000,
        0
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 2
    },
    {
      "id": "b1ab5c2c-f7df-4f2b-bf2d-e3f11a76b691",
      "name": "OpenAI Chat Model",
      "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": "Requête vers la page de l'article",
      "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": "Extraire le contenu",
      "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": "Séparer toutes les sections",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        660,
        0
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "sections"
      },
      "typeVersion": 1
    },
    {
      "id": "047ca863-0ffc-40e2-ac1e-57cdea011063",
      "name": "Supprimer les liens inutiles",
      "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": "Agréger le contenu résumé",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        1300,
        0
      ],
      "parameters": {
        "options": {},
        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "response.text"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "f836d2c0-a28c-4704-a2cc-ec13e3dabfd7",
      "name": "Réorganiser le résumé de l'article",
      "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": "Extracteur de contenu",
      "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": "OpenAI Chat Model1",
      "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": "Répondre à 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": {
    "b82b133e-b2e5-4ed6-9157-f0b4cdd3e4d3": {
      "main": [
        [
          {
            "node": "da17d97e-218a-466d-b356-ccdb63120626",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "034a05a8-78ef-4037-a41d-e2ae7e747378": {
      "main": [
        [
          {
            "node": "88cae164-4e9c-40ab-bbd7-b070863d222d",
            "type": "main",
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        ]
      ]
    },
    "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8": {
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            "index": 0
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        ]
      ]
    },
    "b1ab5c2c-f7df-4f2b-bf2d-e3f11a76b691": {
      "ai_languageModel": [
        [
          {
            "node": "cf2bfb6d-c5ae-46e8-9382-274f37129291",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "71e4f88d-a13f-4d1e-a6af-73c3570dc1b7": {
      "ai_languageModel": [
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          {
            "node": "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8",
            "type": "ai_languageModel",
            "index": 0
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    },
    "cf2bfb6d-c5ae-46e8-9382-274f37129291": {
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            "type": "main",
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    "047ca863-0ffc-40e2-ac1e-57cdea011063": {
      "main": [
        [
          {
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            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "da17d97e-218a-466d-b356-ccdb63120626": {
      "main": [
        [
          {
            "node": "034a05a8-78ef-4037-a41d-e2ae7e747378",
            "type": "main",
            "index": 0
          }
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    },
    "88cae164-4e9c-40ab-bbd7-b070863d222d": {
      "main": [
        [
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            "type": "main",
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    },
    "f836d2c0-a28c-4704-a2cc-ec13e3dabfd7": {
      "main": [
        [
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            "node": "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8",
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    "3ccb4f31-fd75-4eac-be93-08b22c48ea7f": {
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    }
  }
}
Foire aux questions

Comment utiliser ce workflow ?

Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.

Dans quelles scénarios ce workflow est-il adapté ?

Intermédiaire - Intelligence Artificielle

Est-ce payant ?

Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.

Informations sur le workflow
Niveau de difficulté
Intermédiaire
Nombre de nœuds12
Catégorie1
Types de nœuds11
Description de la difficulté

Adapté aux utilisateurs expérimentés, avec des workflows de complexité moyenne contenant 6-15 nœuds

Auteur

12 years in development, South Korea, Seoul

Liens externes
Voir sur n8n.io

Partager ce workflow

Catégories

Catégories: 34