"""ICP scoring — deterministic, explainable account prioritization.

Score 0-100 from additive signals with the breakdown preserved, so sales can
see WHY an account scored what it scored. Labels: A ≥ 75, B ≥ 50, C ≥ 30.
"""
from typing import Any, Dict

from ..config import settings
from ..stores import embeddings


def score_account(account: Dict[str, Any], contact_count: int = 0) -> Dict[str, Any]:
    breakdown: Dict[str, float] = {}

    industry = str(account.get("industry") or "").lower()
    hit = next((x for x in settings.icp_industries_list if x and x in industry), None)
    breakdown["industry_fit"] = 20.0 if hit else 0.0

    country = str(account.get("hq_country") or "").lower()
    breakdown["geo_fit"] = 15.0 if any(x in country for x in settings.icp_countries_list if x) else 0.0

    headcount = account.get("employee_count")
    if isinstance(headcount, str) and headcount.isdigit():
        headcount = int(headcount)
    if isinstance(headcount, (int, float)) and headcount:
        lo, hi = settings.icp_min_headcount, settings.icp_max_headcount
        breakdown["size_band"] = 15.0 if lo <= headcount <= hi else 5.0
    else:
        breakdown["size_band"] = 0.0

    breakdown["digital_presence"] = 15.0 if (account.get("domain") or account.get("website")) else 0.0

    rating = account.get("rating")
    if isinstance(rating, (int, float)) and rating:
        # Google rating (1-5) → up to 10 points; presence alone is a weak signal
        breakdown["market_signal"] = min(max((rating - 3.0) / 2.0, 0.0), 1.0) * 10.0
    elif isinstance(rating, str) and rating.replace(".", "").isdigit():
        breakdown["market_signal"] = min(max((float(rating) - 3.0) / 2.0, 0.0), 1.0) * 10.0
    else:
        breakdown["market_signal"] = 0.0

    breakdown["contact_coverage"] = min(contact_count, 5) * 2.0  # up to 10

    score = round(min(sum(breakdown.values()), 100.0), 1)
    label = "A" if score >= 75 else "B" if score >= 50 else "C" if score >= 30 else "D"
    return {
        "icp_score": score,
        "icp_label": label,
        "breakdown": {k: round(v, 1) for k, v in breakdown.items()},
        "scoring_version": "icp-v1",
    }


def account_text(account: Dict[str, Any]) -> str:
    """The text that represents an account in the vector memory."""
    parts = [
        account.get("name") or "",
        account.get("industry") or "",
        account.get("description") or "",
        f"domain {account.get('domain')}" if account.get("domain") else "",
        f"city {account.get('city')}" if account.get("city") else "",
        f"country {account.get('hq_country')}" if account.get("hq_country") else "",
    ]
    return ". ".join(p for p in parts if p)


def embed_account(account: Dict[str, Any]):
    return embeddings.embed(account_text(account))