"""
Database models for chatbot module
"""
from sqlalchemy import Column, Integer, String, Text, Boolean, DateTime, JSON, ForeignKey
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base
from datetime import datetime
import uuid

from app.db.database import Base

class ChatbotInstance(Base):
    """Configured chatbot instance"""
    __tablename__ = "chatbot_instances"
    
    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
    name = Column(String(255), nullable=False)
    description = Column(Text)
    
    # Configuration stored as JSON
    config = Column(JSON, nullable=False)
    
    # Metadata
    created_by = Column(String, nullable=False)  # User ID
    created_at = Column(DateTime, default=datetime.utcnow)
    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
    is_active = Column(Boolean, default=True)
    
    # Relationships
    conversations = relationship("ChatbotConversation", back_populates="chatbot", cascade="all, delete-orphan")
    
    def __repr__(self):
        return f"<ChatbotInstance(id='{self.id}', name='{self.name}')>"


class ChatbotConversation(Base):
    """Conversation state and history"""
    __tablename__ = "chatbot_conversations"
    
    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
    chatbot_id = Column(String, ForeignKey("chatbot_instances.id"), nullable=False)
    user_id = Column(String, nullable=False)  # User ID
    
    # Conversation metadata
    title = Column(String(255))  # Auto-generated or user-defined title
    created_at = Column(DateTime, default=datetime.utcnow)
    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
    is_active = Column(Boolean, default=True)
    
    # Conversation context and settings
    context_data = Column(JSON, default=dict)  # Additional context
    
    # Relationships
    chatbot = relationship("ChatbotInstance", back_populates="conversations")
    messages = relationship("ChatbotMessage", back_populates="conversation", cascade="all, delete-orphan")
    
    def __repr__(self):
        return f"<ChatbotConversation(id='{self.id}', chatbot_id='{self.chatbot_id}')>"


class ChatbotMessage(Base):
    """Individual chat messages in conversations"""
    __tablename__ = "chatbot_messages"
    
    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
    conversation_id = Column(String, ForeignKey("chatbot_conversations.id"), nullable=False)
    
    # Message content
    role = Column(String(20), nullable=False)  # 'user', 'assistant', 'system'
    content = Column(Text, nullable=False)
    
    # Metadata
    timestamp = Column(DateTime, default=datetime.utcnow)
    message_metadata = Column(JSON, default=dict)  # Token counts, model used, etc.
    
    # RAG sources if applicable
    sources = Column(JSON)  # RAG sources used for this message
    
    # Relationships
    conversation = relationship("ChatbotConversation", back_populates="messages")
    
    def __repr__(self):
        return f"<ChatbotMessage(id='{self.id}', role='{self.role}')>"


class ChatbotAnalytics(Base):
    """Analytics and metrics for chatbot usage"""
    __tablename__ = "chatbot_analytics"
    
    id = Column(Integer, primary_key=True, autoincrement=True)
    chatbot_id = Column(String, ForeignKey("chatbot_instances.id"), nullable=False)
    user_id = Column(String, nullable=False)
    
    # Event tracking
    event_type = Column(String(50), nullable=False)  # 'message_sent', 'response_generated', etc.
    event_data = Column(JSON, default=dict)
    
    # Performance metrics
    response_time_ms = Column(Integer)
    token_count = Column(Integer)
    cost_cents = Column(Integer)
    
    # Context
    model_used = Column(String(100))
    rag_used = Column(Boolean, default=False)
    
    timestamp = Column(DateTime, default=datetime.utcnow)
    
    def __repr__(self):
        return f"<ChatbotAnalytics(id={self.id}, event_type='{self.event_type}')>"