fix: prevent HF 502 by removing sklearn import at startup and hardening DB init

backend/app/database/database.py

@@ -12,7 +12,11 @@ BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__fil
 sqlite_db_path = os.path.join(BASE_DIR, "bankbot.db")
 
 if USE_SQLITE:
-    SQLALCHEMY_DATABASE_URL = f"sqlite:///{sqlite_db_path}"
+    env_db = os.getenv("DATABASE_URL", "")
+    if env_db.startswith("sqlite:"):
+        SQLALCHEMY_DATABASE_URL = env_db
+    else:
+        SQLALCHEMY_DATABASE_URL = f"sqlite:///{sqlite_db_path}"
 
 connect_args = {}
 if "sqlite" in SQLALCHEMY_DATABASE_URL:

backend/app/loans/router.py

@@ -6,7 +6,7 @@ from sqlalchemy.orm import Session
 
 from app.database.database import get_db
 from app.database.models import User
-from app.ai.loan_predictor import calculate_loan_eligibility, generate_loan_comparison
+from app.loans.service import analyze_loan
 
 router = APIRouter(prefix="/api/loans", tags=["Loans"])
 
@@ -36,7 +36,7 @@ def loan_eligibility(
     db: Session = Depends(get_db),
 ):
     _resolve_user(db, user_id)
-    result = calculate_loan_eligibility(
+    return analyze_loan(
         body.salary,
         body.credit_score,
         body.existing_loans,
@@ -44,8 +44,6 @@ def loan_eligibility(
         body.age,
         body.loan_amount,
     )
-    comparison = generate_loan_comparison(body.loan_amount)
-    return {**result, "comparison": comparison[:12]}
 
 
 @router.get("/comparison")
@@ -55,4 +53,5 @@ def loan_comparison(
     db: Session = Depends(get_db),
 ):
     _resolve_user(db, user_id)
-    return {"loan_amount": loan_amount, "comparison": generate_loan_comparison(loan_amount)}
+    result = analyze_loan(85000, 720, 1, 4, 32, loan_amount)
+    return {"loan_amount": loan_amount, "comparison": result["comparison"]}

backend/app/loans/service.py

@@ -0,0 +1,109 @@
+"""Loan eligibility without heavy ML deps (safe for HF Docker)."""
+
+
+def calculate_emi(principal: float, rate_percent: float, tenure_years: int) -> float:
+    if rate_percent <= 0:
+        months = tenure_years * 12
+        return principal / months if months else principal
+    monthly_rate = rate_percent / 100 / 12
+    months = tenure_years * 12
+    if monthly_rate == 0:
+        return principal / months
+    return principal * monthly_rate * ((1 + monthly_rate) ** months) / (((1 + monthly_rate) ** months) - 1)
+
+
+def analyze_loan(
+    salary: float,
+    credit_score: int,
+    existing_loans: int,
+    employment_years: float,
+    age: int,
+    loan_amount: float,
+) -> dict:
+    issues: list[str] = []
+    score = 50.0
+
+    if credit_score >= 750:
+        score += 20
+    elif credit_score >= 700:
+        score += 12
+    elif credit_score >= 650:
+        score += 5
+    else:
+        score -= 10
+        issues.append("Credit score below 650 — consider improving before applying")
+
+    if employment_years >= 3:
+        score += 10
+    elif employment_years < 1:
+        score -= 8
+        issues.append("Less than 1 year employment — higher scrutiny expected")
+
+    if age < 21 or age > 65:
+        issues.append("Age outside typical lending range (21–65)")
+
+    if existing_loans > 3:
+        score -= 12
+        issues.append("Multiple existing loans may reduce approval odds")
+
+    emi = calculate_emi(loan_amount, 12, 10)
+    monthly_salary = salary / 12
+    emi_ratio = (emi / monthly_salary * 100) if monthly_salary > 0 else 100
+
+    if emi_ratio > 50:
+        score -= 15
+        issues.append(f"EMI is {emi_ratio:.0f}% of monthly income — reduce loan amount")
+    elif emi_ratio < 35:
+        score += 8
+
+    if loan_amount > salary * 5:
+        score -= 10
+        issues.append("Loan amount exceeds 5× annual salary")
+
+    score = max(0, min(100, score))
+    approval_probability = score
+
+    if approval_probability >= 70:
+        status = "APPROVED"
+        risk = "Low"
+    elif approval_probability >= 45:
+        status = "UNDER REVIEW"
+        risk = "Medium"
+    else:
+        status = "LIKELY REJECTED"
+        risk = "High"
+
+    recommendations = []
+    if approval_probability >= 70:
+        recommendations.append("Strong profile — you are likely to qualify at competitive rates")
+    elif approval_probability < 45:
+        recommendations.append("Consider a smaller loan or improving credit score before applying")
+    if emi_ratio < 35:
+        recommendations.append(f"Healthy EMI ratio ({emi_ratio:.0f}% of monthly income)")
+    elif emi_ratio > 40:
+        recommendations.append("Try a longer tenure or lower amount to reduce monthly EMI")
+
+    comparison = []
+    for rate in (9, 10, 11, 12):
+        for tenure in (5, 7, 10):
+            e = calculate_emi(loan_amount, rate, tenure)
+            total = e * 12 * tenure
+            comparison.append({
+                "rate": f"{rate}%",
+                "tenure": f"{tenure} years",
+                "emi": round(e, 2),
+                "total_amount": round(total, 2),
+                "interest": round(total - loan_amount, 2),
+            })
+
+    return {
+        "approval_probability": round(approval_probability, 1),
+        "approval_status": status,
+        "risk_level": risk,
+        "loan_score": round(score, 1),
+        "emi": round(emi, 2),
+        "monthly_emi": round(emi, 2),
+        "issues": issues,
+        "recommendations": recommendations,
+        "comparison": comparison[:12],
+    }

backend/app/main.py

@@ -111,8 +111,11 @@ async def rate_limit(request: Request, call_next):
 def startup():
     api_logger.info("BankBot API starting", extra={"version": "2.0.0"})
     Base.metadata.create_all(bind=engine)
-    from app.database.chat_migrate import migrate_chat_schema
-    migrate_chat_schema()
+    try:
+        from app.database.chat_migrate import migrate_chat_schema
+        migrate_chat_schema()
+    except Exception as exc:
+        api_logger.warning("Chat schema migrate skipped", extra={"error": str(exc)[:200]})
     api_logger.info("Database tables ready")
 
     # Log active backends

hf/start.sh

@@ -3,7 +3,7 @@
 # BankBot AI — Hugging Face Spaces startup script
 # Runs: DB init → optional seed → supervisord (nginx + fastapi + nextjs)
 # ============================================================
-set -e
+set -euo pipefail
 
 echo "============================================"
 echo " BankBot AI — Starting on Hugging Face"
@@ -57,9 +57,11 @@ cd /app/backend
 python -c "
 from app.database.database import engine, Base
 import app.database.models
+from app.database.chat_migrate import migrate_chat_schema
 Base.metadata.create_all(bind=engine)
+migrate_chat_schema()
 print('  Database tables ready')
-"
+" || { echo "[WARN] DB init had errors — continuing"; }
 
 # ── Seed demo data (only if DB is empty) ─────────────────────────────────────
 echo "[2/3] Checking demo data..."
@@ -87,7 +89,7 @@ if count == 0:
         print('  Demo account ready: alex@bankbot.dev / BankBot2026!')
 else:
     print(f'  Database has {count} users — skipping seed')
-"
+" || echo "[WARN] Seed check failed — continuing"
 
 # ── Start all services via supervisord ───────────────────────────────────────
 echo "[3/3] Starting services (Nginx + FastAPI + Next.js)..."