import uuid
from datetime import datetime

from sqlalchemy import String, Boolean, Integer, Float, DateTime, ForeignKey, Index, func, Text
from sqlalchemy import Uuid, JSON
from sqlalchemy.orm import Mapped, mapped_column, relationship

from app.database import Base
from app.utils.text import sanitize_raw_response


class CitationRecord(Base):
    __tablename__ = "citation_records"

    id: Mapped[uuid.UUID] = mapped_column(
        Uuid(as_uuid=True),
        primary_key=True,
        default=uuid.uuid4,
    )
    query_id: Mapped[uuid.UUID] = mapped_column(
        Uuid(as_uuid=True),
        ForeignKey("queries.id", ondelete="CASCADE"),
        nullable=False,
    )
    platform: Mapped[str] = mapped_column(String(50), nullable=False)
    cited: Mapped[bool] = mapped_column(Boolean, default=False, nullable=False)
    citation_position: Mapped[int | None] = mapped_column(Integer, nullable=True)
    citation_text: Mapped[str | None] = mapped_column(Text, nullable=True)
    competitor_brands: Mapped[list] = mapped_column(JSON, default=list)
    raw_response: Mapped[str | None] = mapped_column(Text, nullable=True)
    confidence: Mapped[float | None] = mapped_column(Float, nullable=True)
    match_type: Mapped[str | None] = mapped_column(String(20), nullable=True)
    # 情感分析字段
    sentiment: Mapped[str | None] = mapped_column(
        String(20), nullable=True,
        comment="情感倾向: positive / neutral / negative",
    )
    sentiment_confidence: Mapped[float | None] = mapped_column(
        Float, nullable=True,
        comment="情感分析置信度 0.0-1.0",
    )
    sentiment_key_phrases: Mapped[list | None] = mapped_column(
        JSON, nullable=True,
        comment="关键情感短语列表",
    )
    # 引用源分析字段
    data_source: Mapped[str | None] = mapped_column(
        String(20), nullable=True,
        comment="数据来源类型: ai_platform / search_engine / unknown",
    )
    source_urls: Mapped[list | None] = mapped_column(
        JSON, nullable=True,
        comment="提取的引用URL列表",
    )
    source_titles: Mapped[list | None] = mapped_column(
        JSON, nullable=True,
        comment="提取的引用来源标题列表",
    )
    citation_contexts: Mapped[list | None] = mapped_column(
        JSON, nullable=True,
        comment="引用出现的上下文片段列表",
    )
    ai_response_text: Mapped[str | None] = mapped_column(
        Text, nullable=True,
        comment="AI回答原始文本（去掉data_source标记后的纯文本）",
    )
    queried_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True),
        server_default=func.now(),
        nullable=False,
    )

    query: Mapped["Query"] = relationship("Query", back_populates="citation_records")

    __table_args__ = (
        Index("idx_citation_records_query_id", "query_id"),
        Index("idx_citation_records_queried_at", "queried_at"),
        Index("idx_citation_records_platform", "platform"),
    )

    @classmethod
    def from_citation_result(
        cls,
        query_id: uuid.UUID,
        platform: str,
        result: dict,
    ) -> "CitationRecord":
        """从引用检测结果字典创建 CitationRecord 实例

        统一处理字段映射、默认值和 raw_response / ai_response_text 的清理。

        Args:
            query_id: 关联的查询 ID
            platform: 平台名称
            result: 引用检测结果字典

        Returns:
            CitationRecord 实例（未持久化）
        """
        return cls(
            query_id=query_id,
            platform=platform,
            cited=result.get("cited", False),
            citation_position=result.get("position"),
            citation_text=result.get("citation_text"),
            competitor_brands=result.get("competitor_brands", []),
            raw_response=sanitize_raw_response(result.get("raw_response", "")),
            confidence=result.get("confidence"),
            match_type=result.get("match_type"),
            # 引用源分析字段
            data_source=result.get("data_source"),
            source_urls=result.get("source_urls"),
            source_titles=result.get("source_titles"),
            citation_contexts=result.get("citation_contexts"),
            ai_response_text=sanitize_raw_response(result.get("ai_response_text", "")),
        )