Airline Web Check-in Scraper with AI & Vector DB Storage using n8n

### 📝 Web Check-in Details Extractor (LLM Prompt Guide)

#### ✅ What is this?

This is a powerful AI prompt used inside the **"Basic LLM Chain"** node. It tells the AI how to **extract structured airline web check-in data** (like check-in time, baggage policy, cancellation rules) from messy airline webpages.

#### 🎯 Why is it used?

Airline websites often present data in unstructured formats. This LLM-based step:

* Cleans the content scraped from airline URLs.
* Extracts important travel-related info in a consistent JSON format.
* Helps automate the enrichment of airline data stored in your Google Sheets and Vector DB.

#### 🛠️ How to use it?

1. **Input**: This node receives raw webpage content from the airline’s "Web Check-in URL".
2. **Prompt**: It applies a fixed set of rules (in natural language) to guide the AI to convert the unstructured data into clean JSON.
3. **Output**: The AI returns a **structured JSON** object with fields like:

   * `checkin_url`
   * `baggage_allowance`
   * `refund_policy`
   * `faq`
   * `additional_info`
4. The next nodes save this output to:

   * Google Sheet (for visibility)
   * PGVector (for semantic search)

💡 **Pro Tip:** This works best when the HTML content is readable and includes useful labels like “Check-in”, “Cancellation”, “Support”, etc.