Extracción de contenido de marca, resumen y análisis de sentimiento con Bright Data

Name: Extracción de contenido de marca, resumen y análisis de sentimiento con Bright Data
Rating: 4.5 (10 reviews)
Author: Ranjan Dailata

Avanzado

Este es unAI, Marketingflujo de automatización del dominio deautomatización que contiene 23 nodos.Utiliza principalmente nodos como Set, Function, HttpRequest, ManualTrigger, ReadWriteFile, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Extraer y analizar contenido de marca con Bright Data y Google Gemini

Requisitos previos

•Pueden requerirse credenciales de autenticación para la API de destino
•Clave de API de Google Gemini

Nodos utilizados (23)

Categoría

Inteligencia Artificial

Marketing

Vista previa del flujo de trabajo

Visualización de las conexiones entre nodos, con soporte para zoom y panorámica

Al hacer clic en 'Probar flujo de trabajo'

Extractor de Datos Textuales de Markdown

Establecer URL y Zona de Bright Data

Analizador de Sentimientos de IA con respuesta estructurada

Iniciar una Notificación Webhook para Extracción de Datos Textuales de Markdown

Iniciar una Notificación Webhook para Analizador de Sentimientos de IA

Modelo de Chat Google Gemini para Resumen

Modelo de Chat Google Gemini para Extracción de Datos

Modelo de Chat Google Gemini para Analizador de Sentimientos

Iniciar una Notificación Webhook para Resumen

Ejecutar Solicitud Web de Bright Data

Resumir Contenido

Crear datos binarios para datos textuales

Crear datos binarios para análisis de sentimientos

Escribir el archivo de análisis de sentimientos de IA en disco

Escribir el archivo textual en disco

Crear datos binarios para resumen

Escribir el archivo de resumen en disco

React Flow

Exportar flujo de trabajo

Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo

{
  "id": "wTI77cpLkbxsRQat",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "Brand Content Extract, Summarize & Sentiment Analysis with Bright Data",
  "tags": [
    {
      "id": "Kujft2FOjmOVQAmJ",
      "name": "Engineering",
      "createdAt": "2025-04-09T01:31:00.558Z",
      "updatedAt": "2025-04-09T01:31:00.558Z"
    },
    {
      "id": "ddPkw7Hg5dZhQu2w",
      "name": "AI",
      "createdAt": "2025-04-13T05:38:08.053Z",
      "updatedAt": "2025-04-13T05:38:08.053Z"
    }
  ],
  "nodes": [
    {
      "id": "646ef542-c601-4103-87e6-6fa9616d8c52",
      "name": "Al hacer clic en 'Probar flujo de trabajo'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        120,
        -560
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "00b4ce90-c4f2-41c4-8943-7db3d0c3f81a",
      "name": "Nota adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        100,
        -320
      ],
      "parameters": {
        "width": 400,
        "height": 300,
        "content": "## Note\n\nThis workflow deals with the brand content extraction by utilizing the Bright Data Web Unlocker Product.\n\nThe Basic LLM Chain, Information Extraction, Summarization Chain are being used to demonstrate the usage of the N8N AI capabilities.\n\n**Please make sure to set the web URL of your interest within the \"Set URL and Bright Data Zone\" node and update the Webhook Notification URL**"
      },
      "typeVersion": 1
    },
    {
      "id": "5cc35b9b-7483-404e-96a3-1688f7b9078b",
      "name": "Nota adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        540,
        -320
      ],
      "parameters": {
        "width": 480,
        "height": 300,
        "content": "## LLM Usages\n\nGoogle Gemini Flash Exp model is being used.\n\nBasic LLM Chain Data Extractor.\n\nInformation Extraction is being used for the handling the custom sentiment analysis with the structured response.\n\nSummarization Chain is being used for the creation of a concise summary of the extracted brand content."
      },
      "typeVersion": 1
    },
    {
      "id": "e15f32de-58d9-4ea6-9d5c-f63975d1090d",
      "name": "Extractor de Datos Textuales de Markdown",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        1240,
        -440
      ],
      "parameters": {
        "text": "=You need to analyze the below markdown and convert to textual data. Please do not output with your own thoughts. Make sure to output with textual data only with no links, scripts, css etc.\n\n{{ $json.data }}",
        "messages": {
          "messageValues": [
            {
              "message": "You are a markdown expert"
            }
          ]
        },
        "promptType": "define"
      },
      "typeVersion": 1.6
    },
    {
      "id": "1462cd3b-b1d5-4ddf-9f1e-2b8f20faa19c",
      "name": "Establecer URL y Zona de Bright Data",
      "type": "n8n-nodes-base.set",
      "position": [
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      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "3aedba66-f447-4d7a-93c0-8158c5e795f9",
              "name": "url",
              "type": "string",
              "value": "https://www.amazon.com/TP-Link-Dual-Band-Archer-BE230-HomeShield/dp/B0DC99N2T8"
            },
            {
              "id": "4e7ee31d-da89-422f-8079-2ff2d357a0ba",
              "name": "zone",
              "type": "string",
              "value": "web_unlocker1"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "9783e878-e864-4632-9b89-d78567204053",
      "name": "Analizador de Sentimientos de IA con respuesta estructurada",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        1740,
        100
      ],
      "parameters": {
        "text": "=Perform the sentiment analysis on the below content and output with the structured information.\n\nHere's the content:\n\n{{ $('Perform Bright Data Web Request').item.json.data }}",
        "options": {
          "systemPromptTemplate": "You are an expert sentiment analyzer."
        },
        "schemaType": "manual",
        "inputSchema": "{\n  \"$schema\": \"http://json-schema.org/schema#\",\n  \"title\": \"SentimentAnalysisResponseArray\",\n  \"type\": \"array\",\n  \"items\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"sentiment\": {\n        \"type\": \"string\",\n        \"enum\": [\"Positive\", \"Neutral\", \"Negative\"],\n        \"description\": \"The overall sentiment of the content.\"\n      },\n      \"confidence_score\": {\n        \"type\": \"number\",\n        \"minimum\": 0,\n        \"maximum\": 1,\n        \"description\": \"Confidence score of the sentiment classification.\"\n      },\n      \"sentence\": {\n        \"type\": \"string\",\n        \"description\": \"A natural language statement explaining the sentiment.\"\n      }\n    },\n    \"required\": [\"sentiment\", \"confidence_score\", \"sentence\"],\n    \"additionalProperties\": false\n  }\n}\n"
      },
      "typeVersion": 1
    },
    {
      "id": "41352a53-7821-4247-905e-7995e1e6e382",
      "name": "Iniciar una Notificación Webhook para Extracción de Datos Textuales de Markdown",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
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      ],
      "parameters": {
        "url": "https://webhook.site/3c36d7d1-de1b-4171-9fd3-643ea2e4dd76",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "summary",
              "value": "={{ $json.text }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
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    {
      "id": "9717b5df-f148-4c8c-95d4-cb7c54837228",
      "name": "Iniciar una Notificación Webhook para Analizador de Sentimientos de IA",
      "type": "n8n-nodes-base.httpRequest",
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        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
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              "name": "summary",
              "value": "={{ $json.output }}"
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          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "88733b5f-cbb0-42a6-898c-7a1ccc94bef7",
      "name": "Modelo de Chat Google Gemini para Resumen",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
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      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "560e3d33-61d8-4db6-b1df-89f4e915f3f1",
      "name": "Modelo de Chat Google Gemini para Extracción de Datos",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1320,
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      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
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      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
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      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1820,
        320
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
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      "typeVersion": 1
    },
    {
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      "name": "Iniciar una Notificación Webhook para Resumen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1660,
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      ],
      "parameters": {
        "url": "https://webhook.site/3c36d7d1-de1b-4171-9fd3-643ea2e4dd76",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "summary",
              "value": "={{ $json.response.text }}"
            }
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      "typeVersion": 4.2
    },
    {
      "id": "f3e60ecd-5d07-4df0-a413-327b24db23ab",
      "name": "Ejecutar Solicitud Web de Bright Data",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        560,
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      "parameters": {
        "url": "https://api.brightdata.com/request",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "zone",
              "value": "={{ $json.zone }}"
            },
            {
              "name": "url",
              "value": "={{ $json.url }}?product=unlocker&method=api"
            },
            {
              "name": "format",
              "value": "raw"
            },
            {
              "name": "data_format",
              "value": "markdown"
            }
          ]
        },
        "genericAuthType": "httpHeaderAuth",
        "headerParameters": {
          "parameters": [
            {}
          ]
        }
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "9030085f-5b05-41d9-94ee-668ee29df815",
      "name": "Resumir Contenido",
      "type": "@n8n/n8n-nodes-langchain.chainSummarization",
      "position": [
        1240,
        -980
      ],
      "parameters": {
        "options": {
          "summarizationMethodAndPrompts": {
            "values": {
              "prompt": "Write a concise summary of the following:\n\n\n\"{text}\"\n\n"
            }
          }
        },
        "chunkingMode": "advanced"
      },
      "typeVersion": 2
    },
    {
      "id": "fe93c4a6-de3b-481d-ba6c-5f315f5279c4",
      "name": "Crear datos binarios para datos textuales",
      "type": "n8n-nodes-base.function",
      "position": [
        1720,
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      ],
      "parameters": {
        "functionCode": "items[0].binary = {\n  data: {\n    data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n  }\n};\nreturn items;"
      },
      "typeVersion": 1
    },
    {
      "id": "0811c300-1302-49b5-a334-ac8f960a5b8c",
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      "position": [
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      ],
      "parameters": {
        "functionCode": "items[0].binary = {\n  data: {\n    data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n  }\n};\nreturn items;"
      },
      "typeVersion": 1
    },
    {
      "id": "01d798b7-7c62-4240-9d5e-f2e67ca047ae",
      "name": "Escribir el archivo de análisis de sentimientos de IA en disco",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        2520,
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      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\Brand-Content-Sentiment-Analysis.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "f9faf283-ba8d-48e1-860e-2bb660cb9c1e",
      "name": "Escribir el archivo textual en disco",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        2100,
        -220
      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\Brand-Content-Textual.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "2c47c271-4456-4fc4-9a54-20784365a4af",
      "name": "Crear datos binarios para resumen",
      "type": "n8n-nodes-base.function",
      "position": [
        1660,
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      ],
      "parameters": {
        "functionCode": "items[0].binary = {\n  data: {\n    data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n  }\n};\nreturn items;"
      },
      "typeVersion": 1
    },
    {
      "id": "c5f33f8d-93eb-47ac-a42f-717b39f4d7c2",
      "name": "Escribir el archivo de resumen en disco",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        1880,
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      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\Brand-Content-Summary.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "72938f7b-20c1-45d3-9348-878d6e0b8d60",
      "name": "Nota adhesiva2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1200,
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      ],
      "parameters": {
        "color": 4,
        "width": 1100,
        "height": 460,
        "content": "## Summarization"
      },
      "typeVersion": 1
    },
    {
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      "name": "Nota adhesiva3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1720,
        40
      ],
      "parameters": {
        "color": 6,
        "width": 1000,
        "height": 480,
        "content": "## Sentiment Analysis"
      },
      "typeVersion": 1
    },
    {
      "id": "9c44d01f-e30b-4597-ad74-09fa54b4ec84",
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      "position": [
        1200,
        -520
      ],
      "parameters": {
        "color": 3,
        "width": 1100,
        "height": 480,
        "content": "## Textual Data Extract"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
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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, Marketing

¿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.