# model.py

def score_opportunity(data):
    # Weighted score calculation
    raw_score = (
        0.3 * (data['lead_score'] or 0) +
        0.2 * (data['email_count'] or 0) +
        0.2 * (data['meeting_count'] or 0) -
        0.1 * (data['close_date_gap'] or 0)
    )
    # Extra points if at negotiation stage
    if data['stage'] == "Negotiation":
        raw_score += 10

    # Clip score between 0–100
    raw_score = max(0, min(100, round(raw_score)))

    # Risk classification logic
    if raw_score >= 75:
        risk = "Low"
        recommendation = "✅ High chance of closing. Prioritize this deal."
    elif raw_score >= 50:
        risk = "Medium"
        recommendation = "🔁 Moderate potential. Consider a follow-up soon."
    else:
        risk = "High"
        recommendation = "⚠️ Low potential. Reassess or de-prioritize."

    return {
        "score": raw_score,
        "risk": risk,
        "recommendation": recommendation
    }