# /opt/docker/dev/service_finder/backend/app/models/gamification/validation_rule.py
"""
ValidationRule model — Gamification schema.

Stores dynamic global provider validation rules (thresholds) that drive
the ValidationEngine. Rules are key-value pairs with integer values,
seeded at initialization and editable via the admin panel.

Schema: gamification.validation_rules
"""
from typing import Optional
from datetime import datetime
from sqlalchemy import String, Integer, DateTime, func
from sqlalchemy.orm import Mapped, mapped_column
from app.database import Base


class ValidationRule(Base):
    """
    Global provider validation rules / thresholds.

    Each row defines a single rule_key → rule_value mapping used by
    the ValidationEngine to compute trust scores and auto-approval
    thresholds for service providers.

    Seed data (base rules):
        BOT_BASE_SCORE       = 20   # Default trust score for robot-discovered entries
        FIRST_ENTRY_SCORE    = 40   # Score awarded for the first user entry
        USER_CONFIRM_BASE    = 20   # Base score per user confirmation vote
        AUTO_APPROVE_THRESHOLD = 80 # Minimum validation_level to auto-promote
    """
    __tablename__ = "validation_rules"
    __table_args__ = {"schema": "gamification", "extend_existing": True}

    id: Mapped[int] = mapped_column(Integer, primary_key=True, index=True)
    rule_key: Mapped[str] = mapped_column(
        String(100), unique=True, nullable=False, index=True,
        comment="Unique rule identifier, e.g. 'BOT_BASE_SCORE'"
    )
    rule_value: Mapped[int] = mapped_column(
        Integer, nullable=False, default=0,
        comment="Integer value for this rule (score, threshold, etc.)"
    )
    description: Mapped[Optional[str]] = mapped_column(
        String(500), nullable=True,
        comment="Human-readable description of what this rule controls"
    )
    created_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), server_default=func.now()
    )
    updated_at: Mapped[Optional[datetime]] = mapped_column(
        DateTime(timezone=True), onupdate=func.now()
    )