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

from luxx.core.database import Base


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), ForeignKey("projects.id"), 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 a helpful assistant.")
    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)

    # Relationships
    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.

    content 字段统一使用 JSON 格式存储：
    - text: 文本内容
    - attachments: 附件列表
    - tool_calls: 工具调用列表
    - steps: 处理步骤列表

    participant_id 统一发送者格式：
    - "user:{id}" for users
    - "agent:{id}" for agents
    """
    __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)
    participant_id: Mapped[str] = mapped_column(String(64), nullable=False)  # "user:123" or "agent:abc"
    role: Mapped[str] = mapped_column(String(16), nullable=False)  # user/assistant/system/tool
    content: Mapped[str] = mapped_column(Text, nullable=False, default="")
    sender_name: Mapped[str] = mapped_column(String(50), nullable=False, default="")
    mentions: Mapped[Optional[str]] = mapped_column(Text, nullable=True)  # JSON array
    token_count: Mapped[int] = mapped_column(Integer, default=0)
    usage: Mapped[Optional[str]] = mapped_column(Text, nullable=True)  # JSON
    created_at: Mapped[datetime] = mapped_column(DateTime, default=local_now)

    # Relationships
    conversation: Mapped[Optional["Conversation"]] = relationship("Conversation", back_populates="messages")

    @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 ""

    @property
    def sender_type(self) -> str:
        return self.participant_id.split(":")[0] if ":" in self.participant_id else "user"

    @property
    def sender_id(self) -> str:
        return self.participant_id.split(":")[1] if ":" in self.participant_id else self.participant_id

    def to_dict(self):
        """Convert to dictionary, extracting process_steps for frontend"""
        import json

        result = {
            "id": self.id,
            "conversation_id": self.conversation_id,
            "room_id": self.room_id,
            "target_type": self.target_type,
            "target_id": self.target_id,
            "participant_id": self.participant_id,
            "role": self.role,
            "sender_type": self.sender_type,
            "sender_id": self.sender_id,
            "sender_name": self.sender_name,
            "token_count": self.token_count,
            "created_at": self.created_at.isoformat() if self.created_at else None
        }

        # 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
        try:
            content_obj = json.loads(self.content) if self.content else {}
        except json.JSONDecodeError:
            result["content"] = self.content
            result["text"] = self.content
            result["attachments"] = []
            result["tool_calls"] = []
            result["process_steps"] = []
            return result

        result["text"] = content_obj.get("text", "")
        result["attachments"] = content_obj.get("attachments", [])
        result["tool_calls"] = content_obj.get("tool_calls", [])
        result["process_steps"] = content_obj.get("steps", [])

        if "content" not in result:
            result["content"] = result["text"]

        return result