"""
Session History Models for LightRAG API

This module provides database models for storing chat session history, including:
- Chat sessions for organizing conversations
- Chat messages for storing user/assistant interactions
- Message citations for tracking source references
"""

import uuid
from sqlalchemy import Column, String, Boolean, DateTime, ForeignKey, Text, Integer, Float, JSON
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.orm import relationship, declarative_base
from sqlalchemy.sql import func

Base = declarative_base()


class ChatSession(Base):
    """Chat session model for grouping related conversations."""
    
    __tablename__ = "lightrag_chat_sessions_history"

    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
    user_id = Column(String(255), nullable=False, index=True)
    title = Column(String(255), nullable=True)
    rag_config = Column(JSON, default={})
    summary = Column(Text, nullable=True)
    last_message_at = Column(DateTime(timezone=True), server_default=func.now(), index=True)
    created_at = Column(DateTime(timezone=True), server_default=func.now())

    messages = relationship("ChatMessage", back_populates="session", cascade="all, delete-orphan")


class ChatMessage(Base):
    """Chat message model for storing individual messages in a session."""
    
    __tablename__ = "lightrag_chat_messages_history"

    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
    session_id = Column(UUID(as_uuid=True), ForeignKey("lightrag_chat_sessions_history.id", ondelete="CASCADE"), nullable=False)
    role = Column(String(20), nullable=False)  # user, assistant, system
    content = Column(Text, nullable=False)
    token_count = Column(Integer, nullable=True)
    processing_time = Column(Float, nullable=True)
    created_at = Column(DateTime(timezone=True), server_default=func.now())

    session = relationship("ChatSession", back_populates="messages")
    citations = relationship("MessageCitation", back_populates="message", cascade="all, delete-orphan")


class MessageCitation(Base):
    """Message citation model for tracking source references."""
    
    __tablename__ = "lightrag_message_citations_history"

    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
    message_id = Column(UUID(as_uuid=True), ForeignKey("lightrag_chat_messages_history.id", ondelete="CASCADE"), nullable=False)
    source_doc_id = Column(String(255), nullable=False, index=True)
    file_path = Column(Text, nullable=False)
    chunk_content = Column(Text, nullable=True)
    relevance_score = Column(Float, nullable=True)

    message = relationship("ChatMessage", back_populates="citations")