Textbewertung (Unter-Workflow)

Name: Textbewertung (Unter-Workflow)
Rating: 4.5 (10 reviews)
Author: Open Paws

Fortgeschritten

Dies ist ein Market Research, AI Summarization-Bereich Automatisierungsworkflow mit 9 Nodes. Hauptsächlich werden Set, Merge, Aggregate, HttpRequest, ExecuteWorkflowTrigger und andere Nodes verwendet. Bewertung von Tierschutztexten mit Hugging Face Open Paws KI-Modell

Voraussetzungen

•Möglicherweise sind Ziel-API-Anmeldedaten erforderlich

Verwendete Nodes (9)

ExecuteWorkflowTrigger

Kategorie

Marktforschung

KI-Zusammenfassung

Workflow-Vorschau

Visualisierung der Node-Verbindungen, mit Zoom und Pan

Bei Ausführung durch anderen Arbeitsablauf

Leistungspunktzahl abrufen

Präferenzpunktzahl abrufen

Leistungspunktzahl setzen

Präferenzpunktzahl2 abrufen

Ausgabe setzen

Zweige zusammenführen

Einzelelement erstellen

React Flow

Workflow exportieren

Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n

{
  "id": "DTAMHkTadEbS2Xsv",
  "meta": {
    "instanceId": "26bd595441827fb23edb0643d6d240e79b0b8993d278e90950f16e18bf9e3c4a"
  },
  "name": "Scoring Text (Sub-Workflow)",
  "tags": [],
  "nodes": [
    {
      "id": "a81f2018-ff9d-473e-80d3-c0305b297a58",
      "name": "Bei Ausführung durch anderen Arbeitsablauf",
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "position": [
        -600,
        -20
      ],
      "parameters": {
        "workflowInputs": {
          "values": [
            {
              "name": "text"
            }
          ]
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "a857fd97-8a53-4988-8bf0-dd7425725ca1",
      "name": "Leistungspunktzahl abrufen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -340,
        -120
      ],
      "parameters": {
        "url": "INSERT_YOUR_ENDPOINT_URL_HERE",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"inputs\": {{ JSON.stringify($json.text) }},\n  \"parameters\": {}\n} ",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "authentication": "predefinedCredentialType",
        "headerParameters": {
          "parameters": [
            {
              "name": "Accept",
              "value": "application/json"
            }
          ]
        },
        "nodeCredentialType": "huggingFaceApi"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "obk2OV7pJHPdAiyg",
          "name": "Header Auth account"
        },
        "huggingFaceApi": {
          "id": "N2L9e0Csws9dfDOW",
          "name": "HuggingFaceApi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "f4904bd1-bedb-46d9-84e3-4dcd11fbe7e1",
      "name": "Präferenzpunktzahl abrufen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -340,
        80
      ],
      "parameters": {
        "url": "INSERT_YOUR_ENDPOINT_URL_HERE",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"inputs\": {{ JSON.stringify($json.text) }},\n  \"parameters\": {}\n} ",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "authentication": "predefinedCredentialType",
        "headerParameters": {
          "parameters": [
            {
              "name": "Accept",
              "value": "application/json"
            }
          ]
        },
        "nodeCredentialType": "huggingFaceApi"
      },
      "credentials": {
        "huggingFaceApi": {
          "id": "N2L9e0Csws9dfDOW",
          "name": "HuggingFaceApi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "33699ccd-31f2-4bca-81b8-ad00ca2263ba",
      "name": "Leistungspunktzahl setzen",
      "type": "n8n-nodes-base.set",
      "position": [
        -120,
        -120
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "1ba08ac6-99c3-4e2f-ba46-7f570fa35d10",
              "name": "performance_score",
              "type": "number",
              "value": "={{ $json.score }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "641838ba-ca68-4a0e-b9e0-9be37e4e8c32",
      "name": "Präferenzpunktzahl2 abrufen",
      "type": "n8n-nodes-base.set",
      "position": [
        -120,
        80
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "1ba08ac6-99c3-4e2f-ba46-7f570fa35d10",
              "name": "preference_score",
              "type": "number",
              "value": "={{ $json.score }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "3e215fed-abd6-43c0-b736-deec0d97c5fe",
      "name": "Ausgabe setzen",
      "type": "n8n-nodes-base.set",
      "position": [
        480,
        -20
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "e1f63dc1-ad98-4a18-97f7-9f6053201875",
              "name": "performance_score",
              "type": "number",
              "value": "={{ $json.data[0].performance_score }}"
            },
            {
              "id": "928054ae-545d-43a8-a017-44dcf2bef749",
              "name": "preference_score",
              "type": "number",
              "value": "={{ $json.data[1].preference_score }}"
            },
            {
              "id": "22adbb02-16f4-426d-a2da-c9c18e5fdefe",
              "name": "text",
              "type": "string",
              "value": "={{ $('When Executed by Another Workflow').item.json.text }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "5363b1e5-5045-4a8d-bade-f31e7b44c4b3",
      "name": "Zweige zusammenführen",
      "type": "n8n-nodes-base.merge",
      "position": [
        100,
        -20
      ],
      "parameters": {},
      "typeVersion": 3.2
    },
    {
      "id": "eda4c1b6-3c6a-4c00-8b35-d7a8ba3d3db9",
      "name": "Einzelelement erstellen",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        280,
        -20
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData"
      },
      "typeVersion": 1
    },
    {
      "id": "92b8d2e1-ea97-404f-abcc-997158c4ad3d",
      "name": "Haftnotiz",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1260,
        -180
      ],
      "parameters": {
        "width": 560,
        "height": 460,
        "content": "## Sub-Workflow Setup: Text Scoring Models\n\nTo use the scoring sub-workflow, you’ll need to deploy two Hugging Face regression models as inference endpoints:\n\n1. [**Animal Advocate Preference Prediction (Longform)**](https://huggingface.co/open-paws/animal_advocate_preference_prediction_longform)  \n2. [**Text Performance Prediction (Longform)**](https://huggingface.co/open-paws/text_performance_prediction_longform)\n\n### Steps:\n\n1. Visit each model’s Hugging Face page.\n2. Click the **\"Deploy\"** button to create an **inference endpoint** for each model.\n3. Once deployed, copy the **Inference Endpoint URL** for each model.\n4. Add the URLs to the appropriate fields in the n8n sub-workflow where indicated and add your access token to the Hugging Face API credential type for the HTTP nodes.\n\n> ⚠️ Make sure your Hugging Face account has the necessary permissions to create inference endpoints and that your access token has API access enabled.\n"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "f7607f90-ee08-40f1-9565-0e6caca0c491",
  "connections": {
    "5363b1e5-5045-4a8d-bade-f31e7b44c4b3": {
      "main": [
        [
          {
            "node": "eda4c1b6-3c6a-4c00-8b35-d7a8ba3d3db9",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "eda4c1b6-3c6a-4c00-8b35-d7a8ba3d3db9": {
      "main": [
        [
          {
            "node": "3e215fed-abd6-43c0-b736-deec0d97c5fe",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "f4904bd1-bedb-46d9-84e3-4dcd11fbe7e1": {
      "main": [
        [
          {
            "node": "641838ba-ca68-4a0e-b9e0-9be37e4e8c32",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a857fd97-8a53-4988-8bf0-dd7425725ca1": {
      "main": [
        [
          {
            "node": "33699ccd-31f2-4bca-81b8-ad00ca2263ba",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "641838ba-ca68-4a0e-b9e0-9be37e4e8c32": {
      "main": [
        [
          {
            "node": "5363b1e5-5045-4a8d-bade-f31e7b44c4b3",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "33699ccd-31f2-4bca-81b8-ad00ca2263ba": {
      "main": [
        [
          {
            "node": "5363b1e5-5045-4a8d-bade-f31e7b44c4b3",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a81f2018-ff9d-473e-80d3-c0305b297a58": {
      "main": [
        [
          {
            "node": "a857fd97-8a53-4988-8bf0-dd7425725ca1",
            "type": "main",
            "index": 0
          },
          {
            "node": "f4904bd1-bedb-46d9-84e3-4dcd11fbe7e1",
            "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 - Marktforschung, KI-Zusammenfassung

Ist es kostenpflichtig?

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