feat: Add new analysis documents and update installation scripts for backend integration
This commit introduces several new analysis documents, including Auto-Match Load Performance Analysis, Folder Picker Analysis, Monorepo Migration Summary, and various performance analysis documents. Additionally, the installation scripts are updated to reflect changes in backend service paths, ensuring proper integration with the new backend structure. These enhancements provide better documentation and streamline the setup process for users.
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Tanya
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"""SQLAlchemy models for PunimTag Web - matching desktop schema exactly."""
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from __future__ import annotations
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from datetime import datetime, date
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from typing import TYPE_CHECKING
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from sqlalchemy import (
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Boolean,
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Column,
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Date,
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DateTime,
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ForeignKey,
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Index,
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Integer,
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LargeBinary,
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Numeric,
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Text,
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UniqueConstraint,
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CheckConstraint,
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)
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from sqlalchemy.orm import declarative_base, relationship
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from backend.constants.roles import DEFAULT_USER_ROLE
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if TYPE_CHECKING:
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pass
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Base = declarative_base()
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class Photo(Base):
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"""Photo model - matches desktop schema exactly."""
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__tablename__ = "photos"
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id = Column(Integer, primary_key=True, autoincrement=True, index=True)
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path = Column(Text, unique=True, nullable=False, index=True)
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filename = Column(Text, nullable=False)
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date_added = Column(DateTime, default=datetime.utcnow, nullable=False)
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date_taken = Column(Date, nullable=True, index=True)
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processed = Column(Boolean, default=False, nullable=False, index=True)
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file_hash = Column(Text, nullable=False, index=True)
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media_type = Column(Text, default="image", nullable=False, index=True) # "image" or "video"
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faces = relationship("Face", back_populates="photo", cascade="all, delete-orphan")
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photo_tags = relationship(
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"PhotoTagLinkage", back_populates="photo", cascade="all, delete-orphan"
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)
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favorites = relationship("PhotoFavorite", back_populates="photo", cascade="all, delete-orphan")
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video_people = relationship(
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"PhotoPersonLinkage", back_populates="photo", cascade="all, delete-orphan"
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)
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__table_args__ = (
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Index("idx_photos_processed", "processed"),
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Index("idx_photos_date_taken", "date_taken"),
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Index("idx_photos_date_added", "date_added"),
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Index("idx_photos_file_hash", "file_hash"),
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)
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class Person(Base):
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"""Person model - matches desktop schema exactly."""
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__tablename__ = "people"
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id = Column(Integer, primary_key=True, autoincrement=True, index=True)
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first_name = Column(Text, nullable=False)
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last_name = Column(Text, nullable=False)
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middle_name = Column(Text, nullable=True)
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maiden_name = Column(Text, nullable=True)
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date_of_birth = Column(Date, nullable=True)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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faces = relationship("Face", back_populates="person")
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person_encodings = relationship(
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"PersonEncoding", back_populates="person", cascade="all, delete-orphan"
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)
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video_photos = relationship(
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"PhotoPersonLinkage", back_populates="person", cascade="all, delete-orphan"
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)
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__table_args__ = (
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UniqueConstraint(
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"first_name", "last_name", "middle_name", "maiden_name", "date_of_birth",
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name="uq_people_names_dob"
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),
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)
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class Face(Base):
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"""Face detection model - matches desktop schema exactly."""
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__tablename__ = "faces"
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id = Column(Integer, primary_key=True, autoincrement=True, index=True)
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photo_id = Column(Integer, ForeignKey("photos.id"), nullable=False, index=True)
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person_id = Column(Integer, ForeignKey("people.id"), nullable=True, index=True)
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encoding = Column(LargeBinary, nullable=False)
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location = Column(Text, nullable=False)
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confidence = Column(Numeric, default=0.0, nullable=False)
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quality_score = Column(Numeric, default=0.0, nullable=False, index=True)
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is_primary_encoding = Column(Boolean, default=False, nullable=False)
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detector_backend = Column(Text, default="retinaface", nullable=False)
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model_name = Column(Text, default="ArcFace", nullable=False)
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face_confidence = Column(Numeric, default=0.0, nullable=False)
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exif_orientation = Column(Integer, nullable=True)
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pose_mode = Column(Text, default="frontal", nullable=False, index=True)
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yaw_angle = Column(Numeric, nullable=True)
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pitch_angle = Column(Numeric, nullable=True)
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roll_angle = Column(Numeric, nullable=True)
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landmarks = Column(Text, nullable=True) # JSON string of facial landmarks
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identified_by_user_id = Column(Integer, ForeignKey("users.id"), nullable=True, index=True)
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excluded = Column(Boolean, default=False, nullable=False, index=True) # Exclude from identification
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photo = relationship("Photo", back_populates="faces")
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person = relationship("Person", back_populates="faces")
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person_encodings = relationship(
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"PersonEncoding", back_populates="face", cascade="all, delete-orphan"
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)
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__table_args__ = (
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Index("idx_faces_person_id", "person_id"),
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Index("idx_faces_photo_id", "photo_id"),
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Index("idx_faces_quality", "quality_score"),
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Index("idx_faces_pose_mode", "pose_mode"),
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Index("idx_faces_identified_by", "identified_by_user_id"),
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Index("idx_faces_excluded", "excluded"),
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)
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class PersonEncoding(Base):
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"""Person encoding model - matches desktop schema exactly (was person_encodings)."""
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__tablename__ = "person_encodings"
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id = Column(Integer, primary_key=True, autoincrement=True, index=True)
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person_id = Column(Integer, ForeignKey("people.id"), nullable=False, index=True)
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face_id = Column(Integer, ForeignKey("faces.id"), nullable=False, index=True)
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encoding = Column(LargeBinary, nullable=False)
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quality_score = Column(Numeric, default=0.0, nullable=False, index=True)
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detector_backend = Column(Text, default="retinaface", nullable=False)
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model_name = Column(Text, default="ArcFace", nullable=False)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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person = relationship("Person", back_populates="person_encodings")
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face = relationship("Face", back_populates="person_encodings")
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__table_args__ = (
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Index("idx_person_encodings_person_id", "person_id"),
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Index("idx_person_encodings_quality", "quality_score"),
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)
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class Tag(Base):
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"""Tag model - matches desktop schema exactly."""
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__tablename__ = "tags"
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id = Column(Integer, primary_key=True, autoincrement=True, index=True)
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tag_name = Column(Text, unique=True, nullable=False, index=True)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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photo_tags = relationship(
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"PhotoTagLinkage", back_populates="tag", cascade="all, delete-orphan"
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)
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class PhotoTagLinkage(Base):
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"""Photo-Tag linkage model - matches desktop schema exactly (was phototaglinkage)."""
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__tablename__ = "phototaglinkage"
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linkage_id = Column(Integer, primary_key=True, autoincrement=True)
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photo_id = Column(Integer, ForeignKey("photos.id"), nullable=False, index=True)
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tag_id = Column(Integer, ForeignKey("tags.id"), nullable=False, index=True)
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linkage_type = Column(
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Integer, default=0, nullable=False,
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server_default="0"
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)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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photo = relationship("Photo", back_populates="photo_tags")
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tag = relationship("Tag", back_populates="photo_tags")
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__table_args__ = (
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UniqueConstraint("photo_id", "tag_id", name="uq_photo_tag"),
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CheckConstraint("linkage_type IN (0, 1)", name="ck_linkage_type"),
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Index("idx_photo_tags_tag", "tag_id"),
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Index("idx_photo_tags_photo", "photo_id"),
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)
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class PhotoFavorite(Base):
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"""Photo favorites model - user-specific favorites."""
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__tablename__ = "photo_favorites"
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id = Column(Integer, primary_key=True, autoincrement=True)
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username = Column(Text, nullable=False, index=True)
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photo_id = Column(Integer, ForeignKey("photos.id"), nullable=False, index=True)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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photo = relationship("Photo", back_populates="favorites")
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__table_args__ = (
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UniqueConstraint("username", "photo_id", name="uq_user_photo_favorite"),
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Index("idx_favorites_username", "username"),
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Index("idx_favorites_photo", "photo_id"),
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)
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class User(Base):
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"""User model for main database - separate from auth database users."""
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__tablename__ = "users"
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id = Column(Integer, primary_key=True, autoincrement=True, index=True)
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username = Column(Text, unique=True, nullable=False, index=True)
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password_hash = Column(Text, nullable=False) # Hashed password
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email = Column(Text, unique=True, nullable=False, index=True)
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full_name = Column(Text, nullable=False)
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is_active = Column(Boolean, default=True, nullable=False)
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is_admin = Column(Boolean, default=False, nullable=False, index=True)
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role = Column(
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Text,
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nullable=False,
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default=DEFAULT_USER_ROLE,
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server_default=DEFAULT_USER_ROLE,
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index=True,
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)
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password_change_required = Column(Boolean, default=True, nullable=False, index=True)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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last_login = Column(DateTime, nullable=True)
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__table_args__ = (
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Index("idx_users_username", "username"),
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Index("idx_users_email", "email"),
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Index("idx_users_is_admin", "is_admin"),
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Index("idx_users_password_change_required", "password_change_required"),
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Index("idx_users_role", "role"),
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)
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class PhotoPersonLinkage(Base):
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"""Direct linkage between Video (Photo with media_type='video') and Person.
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This allows identifying people in videos without requiring face detection.
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Only used for videos, not photos (photos use Face model for identification).
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"""
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__tablename__ = "photo_person_linkage"
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id = Column(Integer, primary_key=True, autoincrement=True)
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photo_id = Column(Integer, ForeignKey("photos.id"), nullable=False, index=True)
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person_id = Column(Integer, ForeignKey("people.id"), nullable=False, index=True)
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identified_by_user_id = Column(Integer, ForeignKey("users.id"), nullable=True, index=True)
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created_date = Column(DateTime, default=datetime.utcnow, nullable=False)
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photo = relationship("Photo", back_populates="video_people")
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person = relationship("Person", back_populates="video_photos")
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__table_args__ = (
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UniqueConstraint("photo_id", "person_id", name="uq_photo_person"),
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Index("idx_photo_person_photo", "photo_id"),
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Index("idx_photo_person_person", "person_id"),
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Index("idx_photo_person_user", "identified_by_user_id"),
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)
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class RolePermission(Base):
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"""Role-to-feature permission matrix."""
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__tablename__ = "role_permissions"
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id = Column(Integer, primary_key=True, autoincrement=True)
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role = Column(Text, nullable=False, index=True)
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feature_key = Column(Text, nullable=False, index=True)
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allowed = Column(Boolean, nullable=False, default=False, server_default="0")
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__table_args__ = (
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UniqueConstraint("role", "feature_key", name="uq_role_feature"),
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Index("idx_role_permissions_role_feature", "role", "feature_key"),
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)
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