Files
arrr-erp/app/modules/accounting/internal_model_models.py
T
2026-08-22 21:52:44 +05:30

79 lines
4.1 KiB
Python

from __future__ import annotations
from datetime import datetime, timezone
from sqlalchemy import Boolean, DateTime, Float, ForeignKey, Integer, String, Text
from sqlalchemy.orm import Mapped, mapped_column
from app.core.db.common import CommonBase
class AccountingInternalModel(CommonBase):
__tablename__ = "accounting_internal_models"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
tenant_id: Mapped[int] = mapped_column(ForeignKey("tenants.id", ondelete="CASCADE"), nullable=False, index=True)
version_label: Mapped[str] = mapped_column(String(80), nullable=False, index=True)
algorithm: Mapped[str] = mapped_column(String(80), nullable=False, default="multinomial_nb_v1")
status: Mapped[str] = mapped_column(String(30), nullable=False, default="shadow", index=True)
is_active: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False, index=True)
training_examples: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
validation_examples: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
class_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
vocabulary_size: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
validation_accuracy: Mapped[float] = mapped_column(Float, nullable=False, default=0)
validation_macro_recall: Mapped[float] = mapped_column(Float, nullable=False, default=0)
validation_top2_accuracy: Mapped[float] = mapped_column(Float, nullable=False, default=0)
model_json: Mapped[str] = mapped_column(Text, nullable=False)
metrics_json: Mapped[str | None] = mapped_column(Text, nullable=True)
training_summary_json: Mapped[str | None] = mapped_column(Text, nullable=True)
trained_by_user_id: Mapped[int | None] = mapped_column(
ForeignKey("users.id", ondelete="SET NULL"), nullable=True
)
trained_at_utc: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc), index=True
)
class AccountingInternalPrediction(CommonBase):
__tablename__ = "accounting_internal_predictions"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
tenant_id: Mapped[int] = mapped_column(ForeignKey("tenants.id", ondelete="CASCADE"), nullable=False, index=True)
client_id: Mapped[int] = mapped_column(ForeignKey("clients.id", ondelete="CASCADE"), nullable=False, index=True)
model_id: Mapped[int] = mapped_column(
ForeignKey("accounting_internal_models.id", ondelete="CASCADE"), nullable=False, index=True
)
source_type: Mapped[str] = mapped_column(String(30), nullable=False, index=True)
source_record_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
source_fingerprint: Mapped[str] = mapped_column(String(80), nullable=False, default="", index=True)
predicted_nature_id: Mapped[int | None] = mapped_column(
ForeignKey("accounting_natures.id", ondelete="SET NULL"), nullable=True, index=True
)
predicted_probability: Mapped[float] = mapped_column(Float, nullable=False, default=0)
top2_json: Mapped[str | None] = mapped_column(Text, nullable=True)
explanation_json: Mapped[str | None] = mapped_column(Text, nullable=True)
shadow_mode: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True, index=True)
applied_to_source: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False, index=True)
final_nature_id: Mapped[int | None] = mapped_column(
ForeignKey("accounting_natures.id", ondelete="SET NULL"), nullable=True, index=True
)
prediction_correct: Mapped[bool | None] = mapped_column(Boolean, nullable=True, index=True)
reviewed_by_user_id: Mapped[int | None] = mapped_column(
ForeignKey("users.id", ondelete="SET NULL"), nullable=True
)
reviewed_at_utc: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
created_at_utc: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc), index=True
)