saksham
1a4c80958f
FastAPI + Celery + Next.js + Postgres/Redis app with company monitoring, source collection, LLM-based change analysis, enrichment, and account security (Turnstile, escalating lockout, email verification).
45 lines
1.8 KiB
Python
45 lines
1.8 KiB
Python
from __future__ import annotations
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import uuid
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from typing import Any
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from sqlalchemy import JSON, Enum, Float, ForeignKey, String
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from sqlalchemy.orm import Mapped, mapped_column
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from app.db.base import Base, TimestampMixin, UUIDPrimaryKeyMixin
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from app.models.enums import ChangeStatus, ChangeType, SeverityLevel
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class DetectedChange(Base, UUIDPrimaryKeyMixin, TimestampMixin):
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__tablename__ = "detected_changes"
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company_id: Mapped[uuid.UUID] = mapped_column(
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ForeignKey("companies.id", ondelete="CASCADE"), index=True
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)
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source_id: Mapped[uuid.UUID] = mapped_column(
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ForeignKey("sources.id", ondelete="CASCADE"), index=True
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)
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monitoring_run_id: Mapped[uuid.UUID] = mapped_column(
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ForeignKey("monitoring_runs.id", ondelete="CASCADE"), index=True
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)
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previous_snapshot_id: Mapped[uuid.UUID | None] = mapped_column(
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ForeignKey("snapshots.id", ondelete="SET NULL"), nullable=True
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)
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current_snapshot_id: Mapped[uuid.UUID] = mapped_column(
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ForeignKey("snapshots.id", ondelete="CASCADE")
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)
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change_type: Mapped[ChangeType] = mapped_column(Enum(ChangeType, native_enum=False, length=30))
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raw_diff: Mapped[dict[str, Any]] = mapped_column(JSON, default=dict)
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significance_score: Mapped[float] = mapped_column(Float)
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confidence_score: Mapped[float] = mapped_column(Float)
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severity: Mapped[SeverityLevel] = mapped_column(
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Enum(SeverityLevel, native_enum=False, length=20)
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)
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status: Mapped[ChangeStatus] = mapped_column(
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Enum(ChangeStatus, native_enum=False, length=20), default=ChangeStatus.NEW
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)
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# Short human-readable label, e.g. "3 new job postings detected" -
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# populated deterministically here; Phase 7's LLM may later add a
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# richer "why it matters" narrative on top without replacing this.
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summary: Mapped[str] = mapped_column(String(500))
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