Group Trip Data Extractor

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A production-ready Apify Actor that extracts structured trip information from multiple group trip URLs and enriches data using AI.

Project Structure

AI Group trip extractor/
├── .actor/
│ ├── actor.json # Actor configuration
│ ├── input_schema.json # Input parameter definitions
│ ├── output_schema.json # Output schema forAPI/Console
│ └── dataset_schema.json # Dataset field definitions
├── src/
│ ├── main.js # Core actor logic
│ ├── scraper.js # Web scraping(Cheerio/Playwright)
│ ├── ai-enricher.js # OpenAI integration
│ └── schema.js # Schema validation utilities
├── Dockerfile # Docker build configuration
├── package.json # Dependencies & scripts
└── INPUT.json # Sample input for testing

Features

• Multi-URL Processing: Process multiple trip URLs in a single run
• Intelligent Scraping: Uses Cheerio (fast) or Playwright (JavaScript-heavy pages)
• AI Enrichment: Uses OpenAI to infer missing data (coordinates, country, city, trip type)
• Strict Schema: Fixed 17-field output schema for Excel compatibility
• Error Handling: Never breaks schema - returns empty structured rows on errors
• Test Mode: Quick testing with mock data

Output Schema

Every output item contains exactly these 17 fields:

Input Configuration

{
"tripUrls":[
"https://example-travel.com/trip/himalayan-trek",
"https://example-travel.com/trip/goa-weekend"
],
"openaiApiKey":"sk-...",
"model":"gpt-4o-mini",
"testMode":false,
"maxConcurrency":5,
"requestTimeout":60000,
"usePlaywright":false
}

Input Parameters

How It Works

Step 1: Fetch Data

For each URL, the actor loads the page and extracts:

• Title, description, destination
• Price, dates, duration
• Itinerary, inclusions
• Provider name, images, booking link

Step 2: Clean Data

• Remove HTML tags
• Normalize whitespace
• Keep meaningful content only

Step 3: AI Enrichment

Send extracted content to OpenAI to:

• Map data to required schema
• Infer missing fields (country, state, city, trip_type)
• Generate coordinates from destination
• Normalize currency and dates

Step 4: Output

Each dataset item contains all 17 fields with missing values as empty strings.

Error Handling

• Scraping fails: Returns empty structured row with booking_url
• AI fails: Returns partially mapped data
• Invalid URL: Returns empty structured row
• Schema never breaks: All outputs have exactly 17 fields

Performance

• Handles multiple URLs efficiently
• Configurable concurrency
• Timeout under 5 minutes per URL
• Test mode for quick validation

Local Development

# Install dependencies
npminstall
# Run locally
npm start
# Or with Apify CLI
apify run

Deployment to Apify

# Login to Apify
apify login
# Push to Apify
apify push

Cost Estimation

• Scraping: ~$0.01 per URL (Apify compute)
• AI Enrichment: ~$0.001-0.01 per URL (depends on model)
  • gpt-4o-mini: Most cost-effective
  • gpt-4o: Higher quality, higher cost

License

ISC