d6a156dcd2
Implements the data model from spec §3 in one go so FC-2/FC-3 don't need schema-adding migrations of their own. Artist is the unified entity for both gallery 'artist:' tags and GallerySubscriber Subscriptions (is_subscription flag). ImageProvenance is many-to-one, enabling the enrich-on-duplicate rule for downloaded content that pHash-matches an existing record. The SigLIP embedding column uses pgvector(1152) for SigLIP-so400m; swapping models in FC-2 will require a column-width migration. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
72 lines
2.6 KiB
Python
72 lines
2.6 KiB
Python
"""ImageRecord — the gallery's primary entity, ported from ImageRepo.
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ML fields and thumbnails are declared now (in FC-1) so FC-2 can populate them
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without a schema migration. The SigLIP embedding column uses pgvector's Vector
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type — pgvector extension is enabled in the initial migration.
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"""
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from datetime import datetime
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from pgvector.sqlalchemy import Vector
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from sqlalchemy import (
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JSON,
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BigInteger,
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DateTime,
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Enum,
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ForeignKey,
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Integer,
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String,
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Text,
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func,
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)
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from sqlalchemy.orm import Mapped, mapped_column
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from .base import Base
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ORIGIN_CHOICES = ("downloaded", "imported_filesystem", "uploaded")
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class ImageRecord(Base):
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__tablename__ = "image_record"
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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# On-disk identity
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path: Mapped[str] = mapped_column(Text, nullable=False, unique=True)
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sha256: Mapped[str] = mapped_column(String(64), nullable=False, unique=True, index=True)
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phash: Mapped[str | None] = mapped_column(String(32), nullable=True, index=True)
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size_bytes: Mapped[int] = mapped_column(BigInteger, nullable=False)
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mime: Mapped[str] = mapped_column(String(64), nullable=False)
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width: Mapped[int | None] = mapped_column(Integer, nullable=True)
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height: Mapped[int | None] = mapped_column(Integer, nullable=True)
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# Thumbnail (populated by FC-2)
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thumbnail_path: Mapped[str | None] = mapped_column(Text, nullable=True)
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# Origin / provenance pointers
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origin: Mapped[str] = mapped_column(Enum(*ORIGIN_CHOICES, name="origin_enum"), nullable=False)
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primary_post_id: Mapped[int | None] = mapped_column(
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ForeignKey("post.id", ondelete="SET NULL"), nullable=True, index=True
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)
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# ML fields (populated by FC-2's ml-worker)
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wd14_predictions: Mapped[dict | None] = mapped_column(JSON, nullable=True)
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wd14_model_version: Mapped[str | None] = mapped_column(String(128), nullable=True)
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# 1152 = SigLIP-so400m embedding dim. Swapping models in FC-2 may require
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# a column-width migration.
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siglip_embedding: Mapped[list[float] | None] = mapped_column(Vector(1152), nullable=True)
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siglip_model_version: Mapped[str | None] = mapped_column(String(128), nullable=True)
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# Centroid score cache (populated post-tagging)
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centroid_scores: Mapped[dict | None] = mapped_column(JSON, nullable=True)
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True), nullable=False, server_default=func.now()
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)
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updated_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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nullable=False,
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server_default=func.now(),
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onupdate=func.now(),
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)
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