vent_ai_platform/app/db/models/evaluation.py

from __future__ import annotations

from datetime import datetime

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

from app.db.base import Base, TimestampMixin, UUIDPrimaryKeyMixin


class EvaluationIndicator(UUIDPrimaryKeyMixin, TimestampMixin, Base):
    __tablename__ = "evaluation_indicators"

    mine_id: Mapped[str | None] = mapped_column(
        String(32), ForeignKey("mines.id", ondelete="CASCADE"), nullable=True, index=True
    )
    parent_id: Mapped[str | None] = mapped_column(
        String(32), ForeignKey("evaluation_indicators.id", ondelete="SET NULL"), nullable=True
    )
    code: Mapped[str] = mapped_column(String(64), index=True)
    name: Mapped[str] = mapped_column(String(128))
    dimension: Mapped[str] = mapped_column(String(32), index=True)
    indicator_type: Mapped[str] = mapped_column(String(32), default="quantitative")
    unit: Mapped[str] = mapped_column(String(32), default="")
    formula: Mapped[str] = mapped_column(Text, default="")
    data_source: Mapped[str] = mapped_column(String(255), default="")
    weight: Mapped[float] = mapped_column(Float, default=0)
    min_value: Mapped[float | None] = mapped_column(Float, nullable=True)
    max_value: Mapped[float | None] = mapped_column(Float, nullable=True)
    target_value: Mapped[float | None] = mapped_column(Float, nullable=True)
    weight_method: Mapped[str] = mapped_column(String(32), default="static")
    enabled: Mapped[bool] = mapped_column(Boolean, default=True)
    sort_order: Mapped[int] = mapped_column(Integer, default=0)
    config: Mapped[dict] = mapped_column(JSON, default=dict)


class EvaluationRun(UUIDPrimaryKeyMixin, TimestampMixin, Base):
    __tablename__ = "evaluation_runs"

    mine_id: Mapped[str] = mapped_column(
        String(32), ForeignKey("mines.id", ondelete="CASCADE"), index=True
    )
    run_no: Mapped[str] = mapped_column(String(64), unique=True, index=True)
    period_start: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
    period_end: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
    status: Mapped[str] = mapped_column(String(32), default="pending", index=True)
    total_score: Mapped[float | None] = mapped_column(Float, nullable=True)
    grade: Mapped[str] = mapped_column(String(8), default="")
    summary: Mapped[str] = mapped_column(Text, default="")
    recommendations: Mapped[list] = mapped_column(JSON, default=list)
    weight_snapshot: Mapped[dict] = mapped_column(JSON, default=dict)
    input_snapshot: Mapped[dict] = mapped_column(JSON, default=dict)
    model_output: Mapped[dict] = mapped_column(JSON, default=dict)
    started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
    finished_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
    created_by: Mapped[str] = mapped_column(String(128), default="")


class EvaluationScore(UUIDPrimaryKeyMixin, TimestampMixin, Base):
    __tablename__ = "evaluation_scores"

    run_id: Mapped[str] = mapped_column(
        String(32), ForeignKey("evaluation_runs.id", ondelete="CASCADE"), index=True
    )
    indicator_id: Mapped[str] = mapped_column(
        String(32), ForeignKey("evaluation_indicators.id", ondelete="CASCADE"), index=True
    )
    raw_value: Mapped[float | None] = mapped_column(Float, nullable=True)
    score: Mapped[float | None] = mapped_column(Float, nullable=True)
    weighted_score: Mapped[float | None] = mapped_column(Float, nullable=True)
    weight: Mapped[float | None] = mapped_column(Float, nullable=True)
    level: Mapped[str] = mapped_column(String(16), default="")
    evidence: Mapped[str] = mapped_column(Text, default="")
    metadata_json: Mapped[dict] = mapped_column("metadata", JSON, default=dict)