8
n8n Españolamn8n.com

Extracción y resumen de resultados de búsqueda de Bing Copilot con Gemini AI y Bright Data

Avanzado

Este es unAIflujo de automatización del dominio deautomatización que contiene 19 nodos.Utiliza principalmente nodos como If, Set, Wait, HttpRequest, ManualTrigger, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Extraer y resumir resultados de búsqueda de Bing Copilot con Gemini AI y Bright Data

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

Nodos utilizados (19)

If
Set
Wait
StickyNote
HttpRequest
ManualTrigger
ChainLlm
ChainSummarization
LmChatGoogleGemini
OutputParserStructured
DocumentDefaultDataLoader
TextSplitterRecursiveCharacterTextSplitter

Categoría

Inteligencia Artificial
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
React Flow
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
{
  "id": "AnbedV2Ntx97sfed",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "Extract & Summarize Bing Copilot Search Results with Gemini AI and 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": "5f358132-63bd-4c66-80da-4fb9911f607f",
      "name": "Al hacer clic en 'Probar flujo de trabajo'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -1140,
        400
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "43a157f6-2fb8-4c90-bf5d-92fc64c9df10",
      "name": "Modelo de chat Google Gemini",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "notes": "Gemini Experimental Model",
      "position": [
        760,
        580
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-thinking-exp-01-21"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "notesInFlow": true,
      "typeVersion": 1
    },
    {
      "id": "f2d34617-ea34-4163-b9d5-a35fed807dbb",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        940,
        580
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "707fdb4a-f534-4984-b97d-1839db1afc03",
      "name": "Recursive Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1040,
        800
      ],
      "parameters": {
        "options": {},
        "chunkOverlap": 100
      },
      "typeVersion": 1
    },
    {
      "id": "0440b1dd-ca72-467c-a27a-76609ae08fcf",
      "name": "If",
      "type": "n8n-nodes-base.if",
      "position": [
        -220,
        400
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "6a7e5360-4cb5-4806-892e-5c85037fa71c",
              "operator": {
                "type": "string",
                "operation": "equals"
              },
              "leftValue": "={{ $('Check Snapshot Status').item.json.status }}",
              "rightValue": "ready"
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "a23f3c86-200a-4d3c-a762-51cce158c4dd",
      "name": "Establecer Snapshot Id",
      "type": "n8n-nodes-base.set",
      "position": [
        -700,
        400
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "2c3369c6-9206-45d7-9349-f577baeaf189",
              "name": "snapshot_id",
              "type": "string",
              "value": "={{ $json.snapshot_id }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "cee238ff-f725-4a24-8117-540be1c66a56",
      "name": "Download Snapshot",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        140,
        200
      ],
      "parameters": {
        "url": "=https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }}",
        "options": {
          "timeout": 10000
        },
        "sendQuery": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "queryParameters": {
          "parameters": [
            {
              "name": "format",
              "value": "json"
            }
          ]
        }
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "6bb33d11-7176-4dc7-89fe-1ee794793d3e",
      "name": "Modelo de chat Google Gemini1",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        380,
        380
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "b2309938-eaaf-4d63-b8c8-53666cd57dac",
      "name": "Structured Output Parser",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        540,
        380
      ],
      "parameters": {
        "jsonSchemaExample": "[{\n  \"city\": \"string\",\n  \"hotels\": [\n    {\n      \"name\": \"string\",\n      \"address\": \"string\",\n      \"description\": \"string\",\n      \"website\": \"string\",\n      \"area\": \"string (optional)\"\n    }\n  ]\n}\n]\n"
      },
      "typeVersion": 1.2
    },
    {
      "id": "747b1e50-1cae-4efb-86d3-9221438701cd",
      "name": "Check on the errors",
      "type": "n8n-nodes-base.if",
      "position": [
        -20,
        20
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "b267071c-7102-407b-a98d-f613bcb1a106",
              "operator": {
                "type": "string",
                "operation": "equals"
              },
              "leftValue": "={{ $json.errors.toString() }}",
              "rightValue": "0"
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "0bf63795-1f1d-4d6b-90c1-1effae83fd40",
      "name": "Nota adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1140,
        80
      ],
      "parameters": {
        "width": 400,
        "height": 220,
        "content": "## Note\n\nDeals with the Bing Copilot Search using the Bright Data Web Scraper API.\n\nThe Basic LLM Chain and summarization is done to demonstrate the usage of the N8N AI capabilities.\n\n**Please make sure to update the Webhook Notification URL**"
      },
      "typeVersion": 1
    },
    {
      "id": "3872fb7a-382a-446d-8cb0-6ac5a282a801",
      "name": "Nota adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -620,
        80
      ],
      "parameters": {
        "width": 420,
        "height": 220,
        "content": "## LLM Usages\n\nGoogle Gemini Flash Exp model is being used.\n\nBasic LLM Chain makes use of the Output formatter for formatting the response\n\nSummarization Chain is being used for summarization of the content"
      },
      "typeVersion": 1
    },
    {
      "id": "a1453c72-fef3-4cec-967a-858b28ba31d8",
      "name": "Check Snapshot Status",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -460,
        400
      ],
      "parameters": {
        "url": "=https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }}",
        "options": {},
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "5750853b-a07d-455e-b630-977dd733613e",
      "name": "Structured Data Extractor",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        360,
        200
      ],
      "parameters": {
        "text": "=Extract the content as a structured JSON.\n\nHere's the content - {{ $json.answer_text }}",
        "messages": {
          "messageValues": [
            {
              "message": "You are an expert data formatter"
            }
          ]
        },
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.6
    },
    {
      "id": "a86f935f-fe57-40ea-9197-5f20e3002899",
      "name": "Concise Summary Creator",
      "type": "@n8n/n8n-nodes-langchain.chainSummarization",
      "position": [
        760,
        200
      ],
      "parameters": {
        "options": {
          "summarizationMethodAndPrompts": {
            "values": {
              "prompt": "=Write a concise summary of the following:\n\n\n{{ $('Download Snapshot').item.json.answer_text }}\n\n",
              "combineMapPrompt": "=Write a concise summary of the following:\n\n\n\n\n\nCONCISE SUMMARY: {{ $('Download Snapshot').item.json.answer_text }}"
            }
          }
        },
        "operationMode": "documentLoader"
      },
      "typeVersion": 2
    },
    {
      "id": "848ce4b1-0aed-4af2-bf55-bcdb30bbc88a",
      "name": "Esperar for 30 seconds",
      "type": "n8n-nodes-base.wait",
      "position": [
        -280,
        660
      ],
      "webhookId": "f2aafd71-61f2-4aa4-8290-fa3bbe3d46b9",
      "parameters": {
        "amount": 30
      },
      "typeVersion": 1.1
    },
    {
      "id": "5467a870-0734-457b-909e-be425a432ebf",
      "name": "Structured Data Disparador Webhook Notifier",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        760,
        0
      ],
      "parameters": {
        "url": "https://webhook.site/bc804ce5-4a45-4177-a68a-99c80e5c86e6",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "response",
              "value": "={{ $json.output }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "bf8a4868-ead7-411e-97ba-9faea308d836",
      "name": "Summary Disparador Webhook Notifier",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1140,
        200
      ],
      "parameters": {
        "url": "https://webhook.site/bc804ce5-4a45-4177-a68a-99c80e5c86e6",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "response",
              "value": "={{ $json.output }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "60a59b93-9a7c-4d22-ab66-2249fb9ed27e",
      "name": "Perform a Bing Copilot Request",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -920,
        400
      ],
      "parameters": {
        "url": "https://api.brightdata.com/datasets/v3/trigger",
        "method": "POST",
        "options": {},
        "jsonBody": "[\n  {\n    \"url\": \"https://copilot.microsoft.com/chats\",\n    \"prompt\": \"Top hotels in New York\"\n  }\n]",
        "sendBody": true,
        "sendQuery": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "queryParameters": {
          "parameters": [
            {
              "name": "dataset_id",
              "value": "gd_m7di5jy6s9geokz8w"
            },
            {
              "name": "include_errors",
              "value": "true"
            }
          ]
        },
        "headerParameters": {
          "parameters": [
            {}
          ]
        }
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "4462ae6e-4ecd-4f64-aad8-4aa9e65982b6",
  "connections": {
    "0440b1dd-ca72-467c-a27a-76609ae08fcf": {
      "main": [
        [
          {
            "node": "747b1e50-1cae-4efb-86d3-9221438701cd",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Wait for 30 seconds",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set Snapshot Id": {
      "main": [
        [
          {
            "node": "a1453c72-fef3-4cec-967a-858b28ba31d8",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "cee238ff-f725-4a24-8117-540be1c66a56": {
      "main": [
        [
          {
            "node": "5750853b-a07d-455e-b630-977dd733613e",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "747b1e50-1cae-4efb-86d3-9221438701cd": {
      "main": [
        [
          {
            "node": "cee238ff-f725-4a24-8117-540be1c66a56",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "f2d34617-ea34-4163-b9d5-a35fed807dbb": {
      "ai_document": [
        [
          {
            "node": "a86f935f-fe57-40ea-9197-5f20e3002899",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Wait for 30 seconds": {
      "main": [
        [
          {
            "node": "a1453c72-fef3-4cec-967a-858b28ba31d8",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a1453c72-fef3-4cec-967a-858b28ba31d8": {
      "main": [
        [
          {
            "node": "0440b1dd-ca72-467c-a27a-76609ae08fcf",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a86f935f-fe57-40ea-9197-5f20e3002899": {
      "main": [
        [
          {
            "node": "Summary Webhook Notifier",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "a86f935f-fe57-40ea-9197-5f20e3002899",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "b2309938-eaaf-4d63-b8c8-53666cd57dac": {
      "ai_outputParser": [
        [
          {
            "node": "5750853b-a07d-455e-b630-977dd733613e",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "5750853b-a07d-455e-b630-977dd733613e",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "5750853b-a07d-455e-b630-977dd733613e": {
      "main": [
        [
          {
            "node": "a86f935f-fe57-40ea-9197-5f20e3002899",
            "type": "main",
            "index": 0
          },
          {
            "node": "Structured Data Webhook Notifier",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "60a59b93-9a7c-4d22-ab66-2249fb9ed27e": {
      "main": [
        [
          {
            "node": "Set Snapshot Id",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "707fdb4a-f534-4984-b97d-1839db1afc03": {
      "ai_textSplitter": [
        [
          {
            "node": "f2d34617-ea34-4163-b9d5-a35fed807dbb",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "5f358132-63bd-4c66-80da-4fb9911f607f": {
      "main": [
        [
          {
            "node": "60a59b93-9a7c-4d22-ab66-2249fb9ed27e",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
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

¿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.

Flujos de trabajo relacionados recomendados

Extraer, resumir y analizar reducciones de precios de productos de Amazon con Bright Data
Extraer, resumir y analizar información sobre descuentos de Amazon usando Bright Data y Google Gemini
Set
Wait
Merge
+
Set
Wait
Merge
26 NodosRanjan Dailata
Inteligencia Artificial
Generar historias de empresas de LinkedIn con Bright Data y Google Gemini
Usar Bright Data y Google Gemini para generar historias de empresas desde LinkedIn
If
Set
Wait
+
If
Set
Wait
19 NodosRanjan Dailata
Ventas
Usar Bright Data, Gemini y Pinecone para crear un conjunto de datos vectorial listo para IA para LLMs
Usar Bright Data, Gemini y Pinecone para crear conjuntos de datos vectoriales listos para IA para LLM
Set
Http Request
Manual Trigger
+
Set
Http Request
Manual Trigger
21 NodosRanjan Dailata
Bloques de construcción
Rastreo de datos de empresas de Indeed con consolidación en Airtable, Bright Data y Google Gemini
Extracción y resumen de datos de Indeed utilizando Airtable, Bright Data y Google Gemini
If
Set
Wait
+
If
Set
Wait
19 NodosRanjan Dailata
Recursos Humanos
Extracción y resumen de reseñas de empresas de Yelp con Bright Data y Google Gemini
Extraer y resumir reseñas de negocios de Yelp con Bright Data y Google Gemini
Set
Merge
Http Request
+
Set
Merge
Http Request
12 NodosRanjan Dailata
Inteligencia Artificial
Extractor de estudios de caso legales, minador de datos con Bright Data MCP y Google Gemini
Extractor de estudios de caso legales, minero de datos con Bright Data MCP y Google Gemini
Set
Code
Wait
+
Set
Code
Wait
22 NodosRanjan Dailata
Inteligencia Artificial
Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos19
Categoría1
Tipos de nodos12
Descripción de la dificultad

Adecuado para usuarios avanzados, flujos de trabajo complejos con 16+ nodos

Autor
Ranjan Dailata

Ranjan Dailata

@ranjancse
Enlaces externos
Ver en n8n.io →

Compartir este flujo de trabajo

Categorías

IA Multimodal
1540
Inteligencia Artificial
1108
Creación de contenido
695
Resumen de IA
516
Marketing
419
Chatbot de IA
251
Ingeniería
241
Investigación de mercado
203
Varios
193
Otros
176
Ventas
162
Operaciones de TI
156
Extracción de documentos
147
RAG de IA
146
Bloques de construcción
144
Redes sociales
137
Generación de leads
125
Productividad personal
117
DevOps
111
Recursos Humanos
101
Soporte
97
Nutrición de leads
87
CRM
82
Finanzas
81
Producto
77
Chatbot de soporte
76
Diseño
70
Gestión de tickets
67
Operaciones de seguridad
57
Procesamiento de facturas
53
Comercio de criptomonedas
49
Gestión de archivos
39
Gestión de proyectos
35
Wiki interno
32

Categorías: 34