"""
UserMemory model for storing long-term user memory across conversations
"""

from sqlalchemy import Column, String, Text, Numeric, DateTime, JSON, ForeignKey, UniqueConstraint
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.orm import relationship
from sqlalchemy.sql import func
import uuid

from app.database import Base


class UserMemory(Base):
    """
    UserMemory model for storing important user information across conversations

    This enables the bot to remember user preferences, frequently asked questions,
    and important context from previous interactions.
    """

    __tablename__ = "user_memory"

    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True)
    user_id = Column(
        UUID(as_uuid=True),
        ForeignKey("users.id", ondelete="CASCADE"),
        nullable=False,
        index=True
    )

    # Memory key-value pair
    memory_key = Column(String(255), nullable=False, index=True)  # Category or topic
    memory_value = Column(Text, nullable=False)

    # Importance score (0.0 to 1.0)
    importance_score = Column(Numeric(3, 2), default=0.5, nullable=False)

    # Timestamps
    created_at = Column(DateTime(timezone=True), server_default=func.now(), nullable=False)
    updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
    last_accessed_at = Column(DateTime(timezone=True), server_default=func.now())

    # JSON field for additional metadata
    meta_data = Column(JSON, default=dict, nullable=False)

    # Relationships
    user = relationship("User", back_populates="memories")

    # Constraints
    __table_args__ = (
        UniqueConstraint("user_id", "memory_key", name="uq_user_memory_key"),
    )

    def __repr__(self):
        return f"<UserMemory {self.id} - {self.memory_key}>"