"""对话模型 - 用于需求助手和架构助手"""
from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey, Enum
from sqlalchemy.sql import func
from database import Base
import enum


class ConversationType(str, enum.Enum):
    """对话类型"""
    REQUIREMENT = "requirement"  # 需求理解
    ARCHITECTURE = "architecture"  # 架构选型


class Conversation(Base):
    __tablename__ = "conversations"

    id = Column(Integer, primary_key=True, index=True)
    user_id = Column(Integer, ForeignKey("users.id"), nullable=False, index=True)
    title = Column(String(200), default="新对话")
    type = Column(String(20), nullable=False)  # requirement / architecture
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())


class Message(Base):
    __tablename__ = "messages"

    id = Column(Integer, primary_key=True, index=True)
    conversation_id = Column(Integer, ForeignKey("conversations.id"), nullable=False, index=True)
    role = Column(String(20), nullable=False)  # user / assistant
    content = Column(Text, nullable=False)
    image_urls = Column(Text, default="")  # JSON数组，存储图片路径
    created_at = Column(DateTime(timezone=True), server_default=func.now())