Ecommerce Product Rating Protection Agent

import requests, json, numpy as np
from datetime import datetime, timedelta

API_REVIEWS = "https://api.shopee.com/v2/product/reviews"

def fetch_reviews(product_id, days=30):
    resp = requests.get(API_REVIEWS, params={
        "product_id": product_id,
        "since": (datetime.now() - timedelta(days=days)).isoformat()
    })
    return resp.json().get("reviews", [])

def score_authenticity(reviews):
    scores = []
    for r in reviews:
        score = 1.0
        if r.get("reviewer_tenure_days", 365) < 7:
            score -= 0.3
        if len(r.get("text", "")) < 20:
            score -= 0.2
        if r.get("rating") == 5 and r.get("has_images") == False:
            score -= 0.25
        scores.append({"review_id": r["id"], "score": max(0, score)})
    return scores

def flag_suspicious(reviews, threshold=0.5):
    scored = score_authenticity(reviews)
    flagged = [s for s in scored if s["score"] < threshold]
    return {
        "total": len(reviews),
        "flagged": len(flagged),
        "suspicious_ids": [s["review_id"] for s in flagged]
    }

report = flag_suspicious(fetch_reviews("PROD-001"))
print(json.dumps(report, indent=2))