Extract and summarize Wikipedia content with Gemini AI
Workflow Description
Automation that retrieves Wikipedia articles and processes them through Google Gemini for intelligent summarization. Extracts raw content, structures it through language processing chains, and delivers accurate, actionable summaries using advanced AI.
How it works
- 1.Trigger automation manually and input search topic
- 2.Fetch Wikipedia article content via HTTP request
- 3.Process extracted text through LLM processing chain
- 4.Send content to Gemini for intelligent summarization
- 5.Store final summary in variable for downstream use
Use cases
- Quickly gather and summarize Wikipedia research for business reports
- Create objective summaries of scientific and historical articles
- Automate extraction of key information from knowledge sources
Requirements
- Valid Google Gemini API key
- Stable internet connection to access Wikipedia
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (12)
When clicking ‘Test workflow’
Manual Trigger
Google Gemini Chat Model For Summarization
Gemini Model
Google Gemini Chat Model2
Gemini Model
Summary Webhook Notifier
HTTP Request
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Wikipedia Web Request
HTTP Request
LLM Data Extractor
LLM Chain
Concise Summary Generator
Chain Summarization
Set Wikipedia URL with Bright Data Zone
Set
Sticky Note2
Sticky Note
Sticky Note3
Sticky Note