"""语义事实读模型。"""

from __future__ import annotations

from typing import Optional

from sqlalchemy import BigInteger, Boolean, Float, Integer, Text, UniqueConstraint, VARCHAR
from sqlalchemy.orm import Mapped, mapped_column

from .base import Base


class SemanticFact(Base):
    __tablename__ = "semantic_facts"

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    entity_type: Mapped[str] = mapped_column(VARCHAR(32), nullable=False, index=True)
    entity_id: Mapped[int] = mapped_column(BigInteger, nullable=False, index=True)
    fact_namespace: Mapped[str] = mapped_column(VARCHAR(64), nullable=False, index=True)
    fact_key: Mapped[str] = mapped_column(VARCHAR(64), nullable=False, index=True)
    fact_value_text: Mapped[str] = mapped_column(Text, nullable=False)
    fact_value_norm: Mapped[str] = mapped_column(VARCHAR(255), nullable=False, index=True)
    value_type: Mapped[str] = mapped_column(VARCHAR(32), nullable=False, default="keyword")
    confidence: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
    evidence_source_type: Mapped[Optional[str]] = mapped_column(VARCHAR(32), nullable=True)
    evidence_source_id: Mapped[Optional[int]] = mapped_column(BigInteger, nullable=True)
    evidence_excerpt: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
    extract_version: Mapped[Optional[str]] = mapped_column(VARCHAR(64), nullable=True)
    freshness_at: Mapped[Optional[str]] = mapped_column(VARCHAR(64), nullable=True)
    is_active: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True, index=True)

    __table_args__ = (
        UniqueConstraint(
            "tenant_id",
            "entity_type",
            "entity_id",
            "fact_key",
            "fact_value_norm",
            name="uq_semantic_facts_tenant_entity_key_norm",
        ),
    )


__all__ = ["SemanticFact"]