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Extraction et résumé des résultats de recherche Bing Copilot via Gemini AI et Bright Data

Avancé

Ceci est unAIworkflow d'automatisation du domainecontenant 19 nœuds.Utilise principalement des nœuds comme If, Set, Wait, HttpRequest, ManualTrigger, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Extraire et résumer les résultats de recherche Bing Copilot avec Gemini AI et Bright Data

Prérequis
  • •Peut nécessiter les informations d'identification d'authentification de l'API cible
  • •Clé API Google Gemini

Nœuds utilisés (19)

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

Catégorie

Intelligence Artificielle
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
React Flow
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
  "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": "Lors du clic sur 'Tester le workflow'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -1140,
        400
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "43a157f6-2fb8-4c90-bf5d-92fc64c9df10",
      "name": "Google Gemini Chat Model",
      "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": "Chargeur de données par défaut",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        940,
        580
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "707fdb4a-f534-4984-b97d-1839db1afc03",
      "name": "Séparateur de texte récursif",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1040,
        800
      ],
      "parameters": {
        "options": {},
        "chunkOverlap": 100
      },
      "typeVersion": 1
    },
    {
      "id": "0440b1dd-ca72-467c-a27a-76609ae08fcf",
      "name": "Si",
      "type": "n8n-nodes-base.if",
      "position": [
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      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
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          "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": "Définir l'ID de l'instantané",
      "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": "Télécharger l'instantané",
      "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": "Google Gemini Chat Model1",
      "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": "Analyseur de sortie structurée",
      "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": "Vérifier les erreurs",
      "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": "Note autocollante",
      "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": "Note autocollante1",
      "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": "Vérifier l'état de l'instantané",
      "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": "Extracteur de données structurées",
      "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": "Créateur de synthèse concise",
      "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": "Attendre 30 secondes",
      "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": "Notificateur de données structurées Webhook",
      "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": "Notificateur de synthèse Webhook",
      "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": "Effectuer une requête Bing Copilot",
      "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": {
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    "f2d34617-ea34-4163-b9d5-a35fed807dbb": {
      "ai_document": [
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            "node": "a86f935f-fe57-40ea-9197-5f20e3002899",
            "type": "ai_document",
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    "43a157f6-2fb8-4c90-bf5d-92fc64c9df10": {
      "ai_languageModel": [
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    "707fdb4a-f534-4984-b97d-1839db1afc03": {
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            "type": "ai_textSplitter",
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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 ?

Avancé - 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.

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Informations sur le workflow
Niveau de difficulté
Avancé
Nombre de nœuds19
Catégorie1
Types de nœuds12
Description de la difficulté

Adapté aux utilisateurs avancés, avec des workflows complexes contenant 16+ nœuds

Auteur
Ranjan Dailata

Ranjan Dailata

@ranjancse
Liens externes
Voir sur n8n.io →

Partager ce workflow

Catégories

IA Multimodale
1540
Intelligence Artificielle
1108
Création de contenu
695
Résumé IA
516
Marketing
419
Chatbot IA
251
Ingénierie
241
Étude de marché
203
Divers
193
Autres
176
Ventes
162
Opérations IT
156
Extraction de documents
147
RAG IA
146
Blocs de construction
144
Réseaux sociaux
137
Génération de leads
125
Productivité personnelle
117
DevOps
111
Ressources Humaines
101
Support
97
Nurturing de leads
87
CRM
82
Finance
81
Produit
77
Chatbot de support
76
Design
70
Gestion des tickets
67
Opérations de sécurité
57
Traitement des factures
53
Trading crypto
49
Gestion de fichiers
39
Gestion de projet
35
Wiki interne
32

Catégories: 34