Initial commit - MIDAS App educação financeira para apostadores (FastAPI + Next.js)

backend/app/services/risk_engine.py

@@ -0,0 +1,79 @@
+from datetime import datetime, timedelta
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select, func
+from app.models.bet import Bet
+from app.models.bankroll import Bankroll
+
+async def calculate_risk_score(user_id, db: AsyncSession) -> dict:
+    score = 0
+    factors = []
+    now = datetime.utcnow()
+    
+    # 1. Horário noturno (22h-5h) +15
+    hour = now.hour
+    if hour >= 22 or hour < 5:
+        score += 15
+        factors.append("Apostando em horário noturno")
+    
+    # 2. Valor crescente +25
+    recent = await db.execute(
+        select(Bet).where(Bet.user_id == user_id).order_by(Bet.created_at.desc()).limit(5)
+    )
+    recent_bets = recent.scalars().all()
+    if len(recent_bets) >= 3:
+        amounts = [float(b.amount) for b in recent_bets[:3]]
+        if amounts[0] > amounts[1] > amounts[2]:
+            score += 25
+            factors.append("Valores de aposta crescentes")
+    
+    # 3. Recuperação (aposta logo após loss) +30
+    if len(recent_bets) >= 2:
+        last = recent_bets[0]
+        prev = recent_bets[1]
+        if prev.result == "loss" and last.created_at and prev.created_at:
+            diff = (last.created_at - prev.created_at).total_seconds()
+            if diff < 1800:  # 30 min
+                score += 30
+                factors.append("Tentativa de recuperação após perda")
+    
+    # 4. Frequência alta (>5 apostas em 24h) +20
+    day_ago = now - timedelta(hours=24)
+    count_result = await db.execute(
+        select(func.count()).select_from(Bet).where(Bet.user_id == user_id, Bet.created_at >= day_ago)
+    )
+    bet_count = count_result.scalar() or 0
+    if bet_count > 5:
+        score += 20
+        factors.append(f"Alta frequência: {bet_count} apostas em 24h")
+    
+    # 5. Limite estourado +25
+    br_result = await db.execute(select(Bankroll).where(Bankroll.user_id == user_id))
+    bankroll = br_result.scalar_one_or_none()
+    if bankroll and float(bankroll.month_spent) > float(bankroll.monthly_budget):
+        score += 25
+        factors.append("Limite mensal ultrapassado")
+    
+    # 6. Emoção negativa +15
+    if recent_bets and recent_bets[0].emotion in ["😤", "😰", "tilt", "ansioso", "frustrado"]:
+        score += 15
+        factors.append("Emoção negativa detectada")
+    
+    # 7. Sequência de perdas +20
+    loss_streak = 0
+    for b in recent_bets:
+        if b.result == "loss":
+            loss_streak += 1
+        else:
+            break
+    if loss_streak >= 3:
+        score += 20
+        factors.append(f"Sequência de {loss_streak} perdas consecutivas")
+    
+    if score <= 30:
+        level = "green"
+    elif score <= 60:
+        level = "yellow"
+    else:
+        level = "red"
+    
+    return {"score": score, "level": level, "factors": factors}