34 lines
1.5 KiB
Python
34 lines
1.5 KiB
Python
"""Data model representing one persisted processing pipeline log entry."""
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import uuid
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from datetime import UTC, datetime
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from sqlalchemy import BigInteger, DateTime, ForeignKey, String, Text
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from sqlalchemy.dialects.postgresql import JSONB, UUID
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from sqlalchemy.orm import Mapped, mapped_column
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from app.db.base import Base
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class ProcessingLogEntry(Base):
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"""Stores a timestamped processing event with optional model prompt and response text."""
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__tablename__ = "processing_logs"
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id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
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level: Mapped[str] = mapped_column(String(16), nullable=False, default="info")
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stage: Mapped[str] = mapped_column(String(64), nullable=False)
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event: Mapped[str] = mapped_column(String(256), nullable=False)
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document_id: Mapped[uuid.UUID | None] = mapped_column(
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UUID(as_uuid=True),
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ForeignKey("documents.id", ondelete="SET NULL"),
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nullable=True,
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)
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document_filename: Mapped[str | None] = mapped_column(String(512), nullable=True)
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provider_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
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model_name: Mapped[str | None] = mapped_column(String(256), nullable=True)
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prompt_text: Mapped[str | None] = mapped_column(Text, nullable=True)
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response_text: Mapped[str | None] = mapped_column(Text, nullable=True)
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payload_json: Mapped[dict] = mapped_column(JSONB, nullable=False, default=dict)
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