{ "workflow": { "id": 3539, "name": "Extract & summarize Wikipedia data with Bright Data and Gemini AI", "views": 562, "recentViews": 0, "totalViews": 562, "createdAt": "2025-04-13T10:36:32.089Z", "description": "### Who this is for?\nThis workflow automates the process of Wikipedia data extraction using the Bright Data Web Unlocker, parsing and cleaning the data, and then sending the results to a specified webhook URL for downstream processing, reporting, or integration.\n\n### What problem is this workflow solving?\n\n- Researchers who need structured information from Wikipedia pages regularly.\n\n- Data Engineers building knowledge bases or enriching datasets with factual data.\n\n- Digital Marketers or Content Writers automating fact-checking or content sourcing.\n\n- Automation Enthusiasts who want to trigger external systems with rich context from Wikipedia.\n\n### What this workflow does\n\nThis workflow addresses the challenges of manually retrieving, structuring, and using data from Wikipedia at scale.\n\n#### Workflow Breakdown\n\n**Trigger**\n- Type: Scheduled or Manual\n- Purpose: Starts the workflow either on a fixed schedule (e.g., daily) or on-demand via a manual trigger or incoming webhook.\n\n**Bright Data Wikipedia Scraping**\n- Tool Used: Bright Data Web Unlocker\n- Action: Scrape the HTML content of one or multiple Wikipedia article URLs.\n\n**Parse & Extract Structured Data**\n- The Basic LLM Chain node is responsible for producing a human readable content.\n\n**Summarization**\n- Summarize the Wikipedia content by utilizing the Summarization Chain node.\n\n**Send to Webhook**\n- Initiates a Webhook notification to the specified URL as part of the \"**Summary Webhook Notifier**\" node.\n\n### Setup\n\n- Sign up at [Bright Data](https://brightdata.com/).\n- Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.\n- In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication).\n![Header Authentication.png](fileId:1239)\nThe Value field should be set with the\n**Bearer XXXXXXXXXXXXXX**. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token.\n- In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy).\n- Update the **Set Wikipedia URL with Bright Data Zone** node with the Wikipedia URL and Bright Data Zone.\n- Update the **Summary Webhook Notifier** node with the Webhook endpoint of your choice.\n\n### How to customize this workflow to your needs\n\n1. **Update Wikipedia URL**\n- Replace with your own Wikipedia URL of your interest.\n- Make sure to set the Wikipedia URL as part of the \"**Set Wikipedia URL with Bright Data Zone**\" node.\n2. **Modify Data Extraction Logic**\n- Extract entire article content or just specific sections by extending the \"**LLM Data Extractor**\" node prompt.\n3. **Extend AI Summarization**\n- Extract key bullet points or entities.\n- Create short-form summaries by extending the \"**Concise Summary Generator**\" node.\n4. **Extend Summary Webhook Notifier**\n- Send to Slack, Discord, Telegram, MS Teams via the Webhook notification mechanism.\n- Connect to your internal database/API via the Webhook notification mechanism.", "workflow": { "id": "sczRNO4u1HYc5YV7", "meta": { "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40", "templateCredsSetupCompleted": true }, "name": "Extract & Summarize Wikipedia Data with Bright Data and Gemini AI", "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": "0f4b4939-6356-4672-ae61-8d1daf66a168", "name": "When clicking ‘Test workflow’", "type": "n8n-nodes-base.manualTrigger", "position": [ 340, -440 ], "parameters": {}, "typeVersion": 1 }, { "id": "167e060a-c36c-462a-826c-81ef379c824b", "name": "Google Gemini Chat Model For Summarization", "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini", "position": [ 1520, -60 ], "parameters": { "options": {}, "modelName": "models/gemini-2.0-flash-exp" }, "credentials": { "googlePalmApi": { "id": "credential-id", "name": "googlePalmApi Credential" } }, "typeVersion": 1 }, { "id": "a51f2634-8b59-4feb-be39-674e8f198714", "name": "Google Gemini Chat Model2", "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini", "position": [ 1000, -240 ], "parameters": { "options": {}, "modelName": "models/gemini-2.0-pro-exp" }, "credentials": { "googlePalmApi": { "id": "credential-id", "name": "googlePalmApi Credential" } }, "typeVersion": 1 }, { "id": "a1ec001f-6e97-4efb-91d9-9a037fbf472c", "name": "Summary Webhook Notifier", "type": "n8n-nodes-base.httpRequest", "position": [ 1860, -280 ], "parameters": { "url": "https://webhook.site/ce41e056-c097-48c8-a096-9b876d3abbf7", "options": {}, "sendBody": true, "bodyParameters": { "parameters": [ { "name": "summary", "value": "={{ $json.response.text }}" } ] } }, "typeVersion": 4.2 }, { "id": "f4dd93b5-2a33-4ac7-a0c9-9e0956bea363", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ 340, -820 ], "parameters": { "width": 400, "height": 300, "content": "## Note\n\nThis template deals with the Wikipedia data extraction and summarization of content with the Bright Data. \n\nThe LLM Data Extractor is responsible for producing a human readable content.\n\nThe Concise Summary Generator node is responsible for generating the concise summary of the Wikipedia extracted info.\n\n**Please make sure to update the Wikipedia URL with Bright Data Zone. Also make sure to set the Webhook Notification URL.**" }, "typeVersion": 1 }, { "id": "9bd6f913-c526-4e54-81f8-8885a0fe974f", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 780, -820 ], "parameters": { "width": 500, "height": 300, "content": "## LLM Usages\n\nGoogle Gemini Flash Exp model is being used to demonstrate the data extraction and summarization aspects.\n\nBasic LLM Chain is being used for extracting the html to text\n\nSummarization Chain is being used for summarization of the Wikipedia data.\n\n**Note - Replace Google Gemini with the Open AI or suitable LLM providers of your choice.**" }, "typeVersion": 1 }, { "id": "30008ce4-4de2-43c5-bb03-94db58262f86", "name": "Wikipedia Web Request", "type": "n8n-nodes-base.httpRequest", "position": [ 780, -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": "={{ $json.url }}" }, { "name": "format", "value": "raw" } ] }, "genericAuthType": "httpHeaderAuth", "headerParameters": { "parameters": [ {} ] } }, "credentials": { "httpHeaderAuth": { "id": "credential-id", "name": "httpHeaderAuth Credential" } }, "typeVersion": 4.2 }, { "id": "28656a7d-4bd8-41c8-8471-50d19d88e7f2", "name": "LLM Data Extractor", "type": "@n8n/n8n-nodes-langchain.chainLlm", "position": [ 1000, -440 ], "parameters": { "text": "={{ $json.data }}", "messages": { "messageValues": [ { "message": "You are an expert Data Formatter. Make sure to format the data in a human readable manner. Please output the human readable content without your own thoughts" } ] }, "promptType": "define", "hasOutputParser": true }, "typeVersion": 1.6 }, { "id": "7045af3b-9e74-42ef-92f0-f8d3266f2890", "name": "Concise Summary Generator", "type": "@n8n/n8n-nodes-langchain.chainSummarization", "position": [ 1440, -280 ], "parameters": { "options": { "summarizationMethodAndPrompts": { "values": { "prompt": "Write a concise summary of the following:\n\n\n\"{text}\"\n" } } }, "chunkingMode": "advanced" }, "typeVersion": 2 }, { "id": "0cc843c1-252a-4c18-9856-5c7dfc732072", "name": "Set Wikipedia URL with Bright Data Zone", "type": "n8n-nodes-base.set", "notes": "Set the URL which you are interested to scrap the data", "position": [ 560, -440 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "1c132dd6-31e4-453b-a8cf-cad9845fe55b", "name": "url", "type": "string", "value": "https://en.wikipedia.org/wiki/Cloud_computing?product=unlocker&method=api" }, { "id": "0fa387df-2511-4228-b6aa-237cceb3e9c7", "name": "zone", "type": "string", "value": "web_unlocker1" } ] } }, "notesInFlow": true, "typeVersion": 3.4 }, { "id": "6cb9930f-1924-4762-8150-f5cd0e063348", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 940, -500 ], "parameters": { "color": 4, "width": 380, "height": 420, "content": "## Basic LLM Chain Data Extractor\n" }, "typeVersion": 1 }, { "id": "47811535-bce5-4946-aaa6-baef87db1100", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 1400, -340 ], "parameters": { "color": 5, "width": 340, "height": 420, "content": "## Summarization Chain\n" }, "typeVersion": 1 } ], "active": false, "pinData": {}, "settings": { "executionOrder": "v1" }, "versionId": "5b5e78fb-6e5a-4b92-838c-6c4060618e9c", "connections": { "LLM Data Extractor": { "main": [ [ { "node": "Concise Summary Generator", "type": "main", "index": 0 } ] ] }, "Wikipedia Web Request": { "main": [ [ { "node": "LLM Data Extractor", "type": "main", "index": 0 } ] ] }, "Concise Summary Generator": { "main": [ [ { "node": "Summary Webhook Notifier", "type": "main", "index": 0 } ] ] }, "Google Gemini Chat Model2": { "ai_languageModel": [ [ { "node": "LLM Data Extractor", "type": "ai_languageModel", "index": 0 } ] ] }, "When clicking ‘Test workflow’": { "main": [ [ { "node": "Set Wikipedia URL with Bright Data Zone", "type": "main", "index": 0 } ] ] }, "Set Wikipedia URL with Bright Data Zone": { "main": [ [ { "node": "Wikipedia Web Request", "type": "main", "index": 0 } ] ] }, "Google Gemini Chat Model For Summarization": { "ai_languageModel": [ [ { "node": "Concise Summary Generator", "type": "ai_languageModel", "index": 0 } ] ] } } }, "lastUpdatedBy": 29, "workflowInfo": { "nodeCount": 12, "nodeTypes": { "n8n-nodes-base.set": { "count": 1 }, "n8n-nodes-base.stickyNote": { "count": 4 }, "n8n-nodes-base.httpRequest": { "count": 2 }, "n8n-nodes-base.manualTrigger": { "count": 1 }, "@n8n/n8n-nodes-langchain.chainLlm": { "count": 1 }, "@n8n/n8n-nodes-langchain.chainSummarization": { "count": 1 }, "@n8n/n8n-nodes-langchain.lmChatGoogleGemini": { "count": 2 } } }, "status": "published", "user": { "name": "Ranjan Dailata", "username": "ranjancse", "bio": "A Professional based out of India specialized in handling AI-powered automations. 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