Bright Dataを使用してGoogle検索結果ページをスクレイピング
中級
これはAI分野の自動化ワークフローで、12個のノードを含みます。主にSet, HttpRequest, ManualTrigger, Agent, ToolHttpRequestなどのノードを使用、AI技術を活用したスマート自動化を実現。 Bright Dataを利用したGoogle検索結果ページの抽出と要約
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
- •Google Gemini API Key
使用ノード (12)
カテゴリー
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "GcSlNHOnN39cPhRA",
"meta": {
"instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
"templateCredsSetupCompleted": true
},
"name": "Google Search Engine Results Page Extraction 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"
}
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"nodes": [
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"name": "ワークフローをテストする際",
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"position": [
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"parameters": {},
"typeVersion": 1
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{
"id": "d98ae28e-a94f-43a1-9bfe-362adbc61c69",
"name": "Google Gemini チャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
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"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
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"credentials": {
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{
"id": "984acfe6-acd7-4817-b2d5-6d2aab511bae",
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"name": "Google Gemini 要約用チャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
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"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
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"credentials": {
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"typeVersion": 1
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{
"id": "1669f59a-eff8-41ad-a6eb-758eec7ed74a",
"name": "Google Gemini チャットモデル1",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
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"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
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"credentials": {
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"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "ad6c4a15-13e0-49fa-9048-bc1838ba0ef9",
"name": "Webhook HTTP リクエスト",
"type": "@n8n/n8n-nodes-langchain.toolHttpRequest",
"position": [
1960,
-200
],
"parameters": {
"url": "https://webhook.site/ce41e056-c097-48c8-a096-9b876d3abbf7",
"method": "POST",
"sendBody": true,
"parametersBody": {
"values": [
{
"name": "search_summary",
"value": "={{ $json.response.text }}",
"valueProvider": "fieldValue"
},
{
"name": "search_result"
}
]
},
"toolDescription": "Extract the response and format a structured JSON response"
},
"typeVersion": 1.1
},
{
"id": "dc5985c2-02cd-47d0-b518-8dc9d8302998",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
220,
-780
],
"parameters": {
"width": 400,
"height": 300,
"content": "## Bright Data Google Search SERP (Search Engine Results Page)\n\nDeals with the Google Search using the Bright Data Web Scraper API.\n\nThe Information Extraction, Summarization and AI Agent are being used to demonstrate the usage of the N8N AI capabilities.\n\n**Please make sure to Set the Google Search Query and update the Webhook Notification URL**"
},
"typeVersion": 1
},
{
"id": "38b1a20b-9d62-45d9-9399-0b927a6e882a",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"width": 480,
"height": 300,
"content": "## LLM Usages\n\nGoogle Gemini Flash Exp model is being used.\n\nGoogle Search Data Extractor using the n8n Infromation Extractor node.\n\nSummarization Chain is being used for the summarization of search results.\n\nThe AI Agent formats the search result and pushes it to the Webhook via HTTP Request"
},
"typeVersion": 1
},
{
"id": "3019d6eb-cf84-43fd-bb98-f7eed6c9c75f",
"name": "Google 検索データ抽出ツール",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
960,
-440
],
"parameters": {
"text": "={{ $json.data }}",
"options": {
"systemPromptTemplate": "You are an expert HTML extractor. Your job is to analyze the search result and \nstrip out the html, css, scripts and produce a textual data."
},
"attributes": {
"attributes": [
{
"name": "textual_response",
"description": "Textual Response"
}
]
}
},
"typeVersion": 1
},
{
"id": "e82e62cf-6618-405a-943f-d2933771e051",
"name": "Google 検索リクエストの実行",
"type": "n8n-nodes-base.httpRequest",
"position": [
720,
-440
],
"parameters": {
"url": "https://api.brightdata.com/request",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "zone",
"value": "={{ $json.zone }}"
},
{
"name": "url",
"value": "=https://www.google.com/search?q={{ encodeURI($json.search_query) }}"
},
{
"name": "format",
"value": "raw"
}
]
},
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "0d4baa4c-4f6d-4bb2-8964-73d9cf2a391c",
"name": "Google 検索エキスパートAIエージェント",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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],
"parameters": {
"text": "=You are an expert Google Search Expert. You need to format the search result and push it to the Webhook via HTTP Request. Here is the search result - {{ $('Google Search Data Extractor').item.json.output.textual_response }}",
"options": {},
"promptType": "define"
},
"typeVersion": 1.8
},
{
"id": "433d4369-f750-40bd-8e46-8368f535e99f",
"name": "Google 検索クエリの設定",
"type": "n8n-nodes-base.set",
"position": [
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"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "3aedba66-f447-4d7a-93c0-8158c5e795f9",
"name": "search_query",
"type": "string",
"value": "Bright Data"
},
{
"id": "4e7ee31d-da89-422f-8079-2ff2d357a0ba",
"name": "zone",
"type": "string",
"value": "serp_api1"
}
]
}
},
"typeVersion": 3.4
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "3573d57f-de02-4ce6-bfdf-5e83a8a5d7d0",
"connections": {
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}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
中級 - 人工知能
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
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