Automated Airline Web Check-in Scraper with AI and Vector DB Storage
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Streamline airline customer service and operations by automatically scraping web check-in details and policies using AI. This workflow leverages n8n to fetch data from Google Sheets, scrape airline websites, and extract structured information with an LLM, storing it for easy access.
About This Workflow
This n8n workflow automates the tedious process of gathering airline web check-in information and crucial policy details. By integrating with Google Sheets to manage a list of airline URLs, it then utilizes a powerful HTTP request node to scrape each airline's website. The real magic happens with the integration of a Large Language Model (LLM) via the chainLlm node, which intelligently extracts and structures complex data like check-in availability, baggage allowances, refund policies, and customer support information into a clean JSON format. This structured data is ideal for building comprehensive customer-facing knowledge bases, internal operational tools, or for further analysis. The workflow is designed for maximum flexibility and accuracy in handling diverse airline website layouts and information presentation.
Key Features
- Automated Data Collection: Seamlessly fetches airline URLs from Google Sheets.
- Intelligent AI-Powered Extraction: Leverages LLMs to parse unstructured website data into structured JSON.
- Comprehensive Information Retrieval: Extracts details on web check-in, baggage, refunds, customer support, and more.
- Flexible Configuration: Designed to handle varying airline website structures and data points.
- Extensible with Vector DB: Ready for integration with vector databases for advanced search and retrieval capabilities.
How To Use
- Configure Google Sheets Node: Connect your Google Sheets account and specify the Google Sheet and Sheet Name containing your list of airline web check-in URLs.
- Set Up HTTP Request Node: Configure the
httpRequestnode to target the airline website URL. Ensure any necessary cookies or headers are included for successful scraping. You might need to adjust theurlparameter to dynamically use theWEB CHECK IN URLfrom your Google Sheet data. - Integrate LLM for Extraction: In the
chainLlmnode, set thetextparameter to use the scraped content from thehttpRequestnode. Carefully review and customize the providedmessagesprompt to accurately define the desired JSON structure and extraction guidelines for the LLM. - Connect and Run: Link the nodes in sequence:
Chat Trigger->Fetch Airline URLs->Loop Over Items->Scrape Airline Webpage->Extract Info with LLM. Execute the workflow to begin scraping and extracting data. - Store and Utilize Data: The output from the
Extract Info with LLMnode will be a structured JSON object. You can further process this data, store it in a database (including a vector database for semantic search), or integrate it into other applications.
Apps Used
Workflow JSON
{
"id": "1c9c85de-53e9-496a-917a-4419a6473f3e",
"name": "Automated Airline Web Check-in Scraper with AI and Vector DB Storage",
"nodes": 27,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 1c9c85de-53e9...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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