Auto-generate Product Descriptions
from Images with AI

What It Returns

{
  "caption": "A black leather sneaker with white rubber sole and lace-up design",
  "alt_text": "Black leather lace-up sneaker on white background",
  "tags": ["sneaker", "black", "leather", "shoes", "footwear", "lace-up", "casual"],
  "structured": {
    "short_description": "Black leather sneaker with white rubber sole",
    "seo_title": "Black Leather Lace-Up Sneaker | Premium Footwear",
    "meta_description": "Shop our black leather sneaker with white rubber sole and lace-up design. Perfect for casual and street wear."
  },
  "mode": "full",
  "style": "product"
}

Python Example

import requests, time

API_KEY = "YOUR_API_KEY"
BASE = "https://api.pixelapi.dev"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

def caption_product(image_path: str, mode: str = "full") -> dict:
    """Generate caption, tags, and alt text for a product image."""
    with open(image_path, "rb") as f:
        r = requests.post(
            f"{BASE}/v1/image/caption",
            headers=HEADERS,
            files={"image": f},
            data={"mode": mode, "style": "product", "max_tags": 15}
        )
    r.raise_for_status()
    gen_id = r.json()["generation_id"]
    
    # Wait for result
    for _ in range(30):
        status = requests.get(f"{BASE}/v1/generation/{gen_id}", headers=HEADERS).json()
        if status["status"] == "completed":
            result = requests.get(status["output_url"]).json()
            return result
        time.sleep(1)

# Example: Auto-fill product listing
result = caption_product("product.jpg")

print("📝 Description:", result["caption"])
print("🔍 Alt Text:", result["alt_text"])  
print("🏷️  SEO Tags:", ", ".join(result["tags"]))
print("📄 SEO Title:", result["structured"]["seo_title"])

# Bulk: Auto-describe entire catalog
from pathlib import Path
import concurrent.futures

images = list(Path("catalog/").glob("*.jpg"))

def process(img):
    data = caption_product(str(img))
    return {"file": img.name, "caption": data["caption"], "tags": data["tags"]}

with concurrent.futures.ThreadPoolExecutor(max_workers=5) as pool:
    all_results = list(pool.map(process, images))

# Export to CSV for Shopify/WooCommerce import
import csv
with open("product_descriptions.csv", "w", newline="") as csvf:
    writer = csv.DictWriter(csvf, fieldnames=["file","caption","tags"])
    writer.writeheader()
    writer.writerows(all_results)

print(f"✅ Generated descriptions for {len(all_results)} products")
print(f"   Cost: ${len(all_results) * 0.005:.2f}")