Webhook | Abstract der Arbeit

Fortgeschritten

Dies ist ein AI-Bereich Automatisierungsworkflow mit 12 Nodes. Hauptsächlich werden Set, Html, Webhook, SplitOut, Aggregate und andere Nodes verwendet, kombiniert mit KI-Technologie für intelligente Automatisierung. Arxi papierzusammenfassungen mit ChatGPT erstellen

Voraussetzungen
  • HTTP Webhook-Endpunkt (wird von n8n automatisch generiert)
  • Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • OpenAI API Key
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "id": "5IAbyLhZX99QS1ff",
  "meta": {
    "instanceId": "0b0f5302e78710cf1b1457ee15a129d8e5d83d4e366bd96d14cc37da6693e692"
  },
  "name": "Webhook | Paper Summarization",
  "tags": [],
  "nodes": [
    {
      "id": "cf2bfb6d-c5ae-46e8-9382-274f37129291",
      "name": "Zusammenfassungs-Kette",
      "type": "@n8n/n8n-nodes-langchain.chainSummarization",
      "position": [
        1000,
        0
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 2
    },
    {
      "id": "b1ab5c2c-f7df-4f2b-bf2d-e3f11a76b691",
      "name": "OpenAI Chat-Modell",
      "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": "Anfrage an Paper-Seite",
      "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": "Inhalte extrahieren",
      "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": "Alle Abschnitte aufteilen",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        660,
        0
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "sections"
      },
      "typeVersion": 1
    },
    {
      "id": "047ca863-0ffc-40e2-ac1e-57cdea011063",
      "name": "Nutzlose Links entfernen",
      "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": "Zusammengefasste Inhalte aggregieren",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        1300,
        0
      ],
      "parameters": {
        "options": {},
        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "response.text"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "f836d2c0-a28c-4704-a2cc-ec13e3dabfd7",
      "name": "Paper-Zusammenfassung neu strukturieren",
      "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": "Inhalts-Extraktor",
      "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-Modell1",
      "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-Trigger",
      "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": "Antwort an Webhook-Trigger",
      "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": {
    "Webhook": {
      "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",
            "index": 0
          }
        ]
      ]
    },
    "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8": {
      "main": [
        [
          {
            "node": "Antwort an Webhook",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "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": [
        [
          {
            "node": "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "cf2bfb6d-c5ae-46e8-9382-274f37129291": {
      "main": [
        [
          {
            "node": "3ccb4f31-fd75-4eac-be93-08b22c48ea7f",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "047ca863-0ffc-40e2-ac1e-57cdea011063": {
      "main": [
        [
          {
            "node": "cf2bfb6d-c5ae-46e8-9382-274f37129291",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "da17d97e-218a-466d-b356-ccdb63120626": {
      "main": [
        [
          {
            "node": "034a05a8-78ef-4037-a41d-e2ae7e747378",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "88cae164-4e9c-40ab-bbd7-b070863d222d": {
      "main": [
        [
          {
            "node": "047ca863-0ffc-40e2-ac1e-57cdea011063",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "f836d2c0-a28c-4704-a2cc-ec13e3dabfd7": {
      "main": [
        [
          {
            "node": "99d0edeb-5265-45c8-ad5f-7158bbd0e5d8",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "3ccb4f31-fd75-4eac-be93-08b22c48ea7f": {
      "main": [
        [
          {
            "node": "f836d2c0-a28c-4704-a2cc-ec13e3dabfd7",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - Künstliche Intelligenz

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes12
Kategorie1
Node-Typen11
Schwierigkeitsbeschreibung

Für erfahrene Benutzer, mittelkomplexe Workflows mit 6-15 Nodes

Autor

12 years in development, South Korea, Seoul

Externe Links
Auf n8n.io ansehen

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Kategorien

Kategorien: 34