Flag customers who may stop buying

from collections import defaultdict
from datetime import datetime, timedelta, timezone
from clickruntime import on_trigger, credentials, http, ai, notify

API = "https://a.klaviyo.com/api"
PLACED_ORDER_METRIC_ID = "RESQ6t"
WIN_BACK_LIST_ID = "Wb4Lst"

def klaviyo():
    return {"Authorization": f"Klaviyo-API-Key {credentials.secret('KLAVIYO_API_KEY')}",
            "revision": "2024-10-15", "accept": "application/vnd.api+json", "content-type": "application/vnd.api+json"}

@on_trigger
def run(event):
    h = klaviyo()
    since = (datetime.now(timezone.utc) - timedelta(days=365)).strftime("%Y-%m-%dT%H:%M:%SZ")
    url, params, orders = f"{API}/events", {"filter": f'equals(metric_id,"{PLACED_ORDER_METRIC_ID}"),greater-than(datetime,{since})',
                                            "fields[event]": "datetime", "page[size]": 200}, defaultdict(list)
    while url:
        page = http.get(url, headers=h, params=params).json()
        for e in page["data"]:
            orders[e["relationships"]["profile"]["data"]["id"]].append(datetime.fromisoformat(e["attributes"]["datetime"]))
        url, params = page["links"].get("next"), None
    now = datetime.now(timezone.utc)
    quiet = [(pid, sorted(d)) for pid, d in orders.items() if now - max(d) > timedelta(days=60)]
    lines = [f"{i}. orders={len(d)} days_since_last={(now - d[-1]).days} "
             f"avg_gap_days={(d[-1] - d[0]).days // max(len(d) - 1, 1)}" for i, (_, d) in enumerate(quiet[:300])]
    high_risk = []
    if lines:
        r = ai.generate("Each line is a customer's order history. Return the numbers of customers at high churn risk.\n"
                        + "\n".join(lines), max_output_tokens=800,
                        json_schema={"type": "object", "properties": {"high": {"type": "array", "items": {"type": "integer"}}}})
        high_risk = [quiet[i][0] for i in r.json["high"] if i < len(quiet)]
    for i in range(0, len(high_risk), 1000):
        http.post(f"{API}/lists/{WIN_BACK_LIST_ID}/relationships/profiles", headers=h,
                  json={"data": [{"type": "profile", "id": p} for p in high_risk[i:i + 1000]]}).raise_for_status()
    notify.email_me("Win-back list updated", f"Added {len(high_risk)} high-risk customers out of {len(orders)} buyers.")
    return {"added": len(high_risk)}