Cars Test

You are scraping a car dealership inventory website.

Step 1 - Inventory pages:
Go to the inventory page. You will find car listings displayed as cards.
Each card shows the car's basic info and a link to its detail page.
Do NOT follow pagination. Only extract cars from the FIRST page.
Extract only the FIRST 2 cars you find.

For each car, extract the data in this exact JSON format:
{
  "year": 2020,
  "make": "Toyota",
  "model": "4Runner",
  "price": "$34,995.00",
  "detail_url": "https://narrowpath.autos/inventory/40449/view/1657/Birmingham-AL/2020-Toyota-4Runner"
}

Do NOT put any pagination links in next_urls.
Put each car's detail page URL in detail_urls.

Step 2 - Detail pages:
Visit each car's detail page. The detail page has:
- A photo gallery/carousel with multiple car images. Look for all image URLs
  in ![alt](url) markdown patterns, <img> tags, or any URLs ending in
  .jpg, .jpeg, .png, .webp. Collect ALL image URLs, not just the first one.
- A specs/details section with VIN, transmission, colors, drivetrain, fuel type,
  mileage, engine, and other vehicle information.

Extract all available data from the detail page in this JSON format:
{
  "year": 2020,
  "make": "Toyota",
  "model": "4Runner",
  "price": "$34,995.00",
  "detail_url": "https://narrowpath.autos/inventory/40449/view/1657/Birmingham-AL/2020-Toyota-4Runner",
  "images": ["https://example.com/img1.jpg", "https://example.com/img2.jpg"],
  "vin": "JTEBU5JR8L5123456",
  "transmission": "Automatic",
  "exterior_color": "Midnight Black",
  "interior_color": "Black",
  "drivetrain": "4WD",
  "fuel_type": "Gasoline",
  "city_mileage": "16 MPG",
  "highway_mileage": "19 MPG",
  "engine": "4.0L V6",
  "mileage": "45,000"
}