product recommendations API

Sure — I can help with a product recommendations API in a few different ways.

If you mean build one, here’s a simple starting design:

Example endpoints

• GET /products — list products
• GET /recommendations?user_id=123 — personalized recommendations
• GET /recommendations?product_id=456 — similar products
• POST /events — track clicks, views, purchases

Basic recommendation approaches

1. Content-based
   • Recommend products similar in category, brand, price, tags.
2. Collaborative filtering
   • Recommend products bought/viewed by similar users.
3. Popularity-based
   • Recommend trending/top-selling products.
4. Hybrid
   • Combine multiple methods for better quality.

Minimal response example

{
  "user_id": "123",
  "recommendations": [
    {
      "product_id": "p1",
      "name": "Wireless Headphones",
      "score": 0.98
    },
    {
      "product_id": "p2",
      "name": "Bluetooth Speaker",
      "score": 0.91
    }
  ]
}

Example request

GET /recommendations?user_id=123

Example Python/FastAPI sketch

from fastapi import FastAPI

app = FastAPI()

@app.get("/recommendations")
def recommendations(user_id: str):
    return {
        "user_id": user_id,
        "recommendations": [
            {"product_id": "p1", "name": "Wireless Headphones", "score": 0.98},
            {"product_id": "p2", "name": "Bluetooth Speaker", "score": 0.91}
        ]
    }

If you want, I can provide one of these next:

1. Full API design
2. OpenAPI/Swagger spec
3. FastAPI/Node.js implementation
4. Recommendation algorithm design
5. Database schema for recommendation tracking