"""Chat-related models"""
import json
from datetime import datetime
from typing import Optional, List, TYPE_CHECKING
from sqlalchemy import String, Integer, Boolean, Float, Text, DateTime, ForeignKey
from sqlalchemy.orm import Mapped, mapped_column, relationship

from luxx.core.database import Base

if TYPE_CHECKING:
    from luxx.models.user import LLMProvider, User


def local_now():
    return datetime.now()


class Conversation(Base):
    """Conversation model"""
    __tablename__ = "conversations"

    id: Mapped[str] = mapped_column(String(64), primary_key=True)
    user_id: Mapped[int] = mapped_column(Integer, ForeignKey("users.id"), nullable=False)
    provider_id: Mapped[Optional[int]] = mapped_column(Integer, ForeignKey("llm_providers.id"), nullable=True)
    project_id: Mapped[Optional[str]] = mapped_column(String(64), nullable=True)
    title: Mapped[str] = mapped_column(String(255), nullable=False)
    model: Mapped[str] = mapped_column(String(64), nullable=False, default="deepseek-chat")
    system_prompt: Mapped[str] = mapped_column(Text, nullable=False, default="You are helpful.")
    temperature: Mapped[float] = mapped_column(Float, default=0.7)
    max_tokens: Mapped[int] = mapped_column(Integer, default=2000)
    thinking_enabled: Mapped[bool] = mapped_column(Boolean, default=False)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=local_now)
    updated_at: Mapped[datetime] = mapped_column(DateTime, default=local_now, onupdate=local_now)

    user: Mapped["User"] = relationship("User", back_populates="conversations")
    provider: Mapped[Optional["LLMProvider"]] = relationship("LLMProvider")
    messages: Mapped[List["Message"]] = relationship(
        "Message", back_populates="conversation", cascade="all, delete-orphan"
    )

    def to_dict(self):
        return {
            "id": self.id,
            "user_id": self.user_id,
            "provider_id": self.provider_id,
            "project_id": self.project_id,
            "title": self.title,
            "model": self.model,
            "system_prompt": self.system_prompt,
            "temperature": self.temperature,
            "max_tokens": self.max_tokens,
            "thinking_enabled": self.thinking_enabled,
            "created_at": self.created_at.isoformat() if self.created_at else None,
            "updated_at": self.updated_at.isoformat() if self.updated_at else None
        }


class Message(Base):
    """Unified Message model for Conversation and ChatRoom.
    
    统一消息模型，支持:
    - Conversation: 单人会话
    - ChatRoom: 聊天室（多 Agent）
    
    sender_type: user | agent | system
    content: JSON 格式 {"text": "...", "steps": [...]}
    """
    __tablename__ = "messages"

    id: Mapped[str] = mapped_column(String(64), primary_key=True)
    conversation_id: Mapped[Optional[str]] = mapped_column(String(64), ForeignKey("conversations.id"), nullable=True)
    room_id: Mapped[Optional[str]] = mapped_column(String(64), nullable=True)
    
    # 发送者信息
    sender_id: Mapped[str] = mapped_column(String(64), nullable=False, default="")      # 用户ID 或 AgentID
    sender_type: Mapped[str] = mapped_column(String(16), nullable=False, default="user")  # "user" | "agent" | "system"
    sender_name: Mapped[str] = mapped_column(String(50), nullable=False, default="")
    
    # 消息内容（兼容旧格式，同时保留 role 字段用于兼容 Conversation）
    role: Mapped[str] = mapped_column(String(16), nullable=False, default="user")  # 保留，兼容 Conversation
    content: Mapped[str] = mapped_column(Text, nullable=False, default="")
    
    # 流式响应元数据
    is_streaming: Mapped[bool] = mapped_column(Boolean, default=False)
    stream_id: Mapped[Optional[str]] = mapped_column(String(64), nullable=True)
    parent_id: Mapped[Optional[str]] = mapped_column(String(64), nullable=True)  # 回复的消息ID
    
    # 元数据
    mentions: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
    token_count: Mapped[int] = mapped_column(Integer, default=0)
    usage: Mapped[Optional[str]] = mapped_column(Text, nullable=True)

    conversation: Mapped[Optional["Conversation"]] = relationship("Conversation", back_populates="messages")
    created_at: Mapped[datetime] = mapped_column(DateTime, default=local_now)

    @property
    def target_type(self) -> str:
        return "conversation" if self.conversation_id else "room"

    @property
    def target_id(self) -> str:
        return self.conversation_id or self.room_id or ""

    def to_dict(self, include_stream_data: bool = False):
        """转换消息为字典
        
        统一使用 sender 格式，content 保留 JSON 和纯文本两种格式
        """
        result = {
            "id": self.id,
            "conversation_id": self.conversation_id,
            "room_id": self.room_id,
            "target_type": self.target_type,
            "target_id": self.target_id,
            "sender": {
                "id": self.sender_id,
                "type": self.sender_type,
                "name": self.sender_name
            },
            # 兼容字段
            "sender_id": self.sender_id,
            "sender_type": self.sender_type,
            "sender_name": self.sender_name,
            "role": self.role,  # 保留，兼容 Conversation
            "token_count": self.token_count,
            "is_streaming": self.is_streaming,
            "created_at": self.created_at.isoformat() if self.created_at else None
        }
        
        # 流式数据
        if include_stream_data:
            result["stream_id"] = self.stream_id
            result["parent_id"] = self.parent_id

        # Parse usage JSON
        if self.usage:
            try:
                result["usage"] = json.loads(self.usage)
            except json.JSONDecodeError:
                result["usage"] = None

        # Parse mentions JSON
        if self.mentions:
            try:
                result["mentions"] = json.loads(self.mentions)
            except json.JSONDecodeError:
                result["mentions"] = []
        else:
            result["mentions"] = []

        # Parse content JSON - 提取 text 和 steps
        try:
            content_obj = json.loads(self.content) if self.content else {}
            result["content"] = content_obj.get("text", content_obj.get("content", self.content))
            result["text"] = result["content"]
            result["process_steps"] = content_obj.get("steps", content_obj.get("process_steps", []))
            result["attachments"] = content_obj.get("attachments", [])
            result["tool_calls"] = content_obj.get("tool_calls", [])
        except json.JSONDecodeError:
            # 纯文本内容
            result["text"] = self.content
            result["content"] = self.content
            result["process_steps"] = []
            result["attachments"] = []
            result["tool_calls"] = []

        return result