4592e35732
Brain Service: - Playwright stealth crawler replacing browserless (og:image, Readability, Reddit JSON API) - AI classification with tag definitions and folder assignment - YouTube video download via yt-dlp - Karakeep migration complete (96 items) - Taxonomy management (folders with icons/colors, tags) - Discovery shuffle, sort options, search (Meilisearch + pgvector) - Item tag/folder editing, card color accents RSS Reader Service: - Custom FastAPI reader replacing Miniflux - Feed management (add/delete/refresh), category support - Full article extraction via Readability - Background content fetching for new entries - Mark all read with confirmation - Infinite scroll, retention cleanup (30/60 day) - 17 feeds migrated from Miniflux iOS App (SwiftUI): - Native iOS 17+ app with @Observable architecture - Cookie-based auth, configurable gateway URL - Dashboard with custom background photo + frosted glass widgets - Full fitness module (today/templates/goals/food library) - AI assistant chat (fitness + brain, raw JSON state management) - 120fps ProMotion support AI Assistants (Gateway): - Unified dispatcher with fitness/brain domain detection - Fitness: natural language food logging, photo analysis, multi-item splitting - Brain: save/append/update/delete notes, search & answer, undo support - Madiha user gets fitness-only (brain disabled) Firefox Extension: - One-click save to Brain from any page - Login with platform credentials - Right-click context menu (save page/link/image) - Notes field for URL saves - Signed and published on AMO Other: - Reader bookmark button routes to Brain (was Karakeep) - Fitness food library with "Add" button + add-to-meal popup - Kindle send file size check (25MB SMTP2GO limit) - Atelier UI as default (useAtelierShell=true) - Mobile upload box in nav drawer Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
104 lines
4.4 KiB
Python
104 lines
4.4 KiB
Python
"""SQLAlchemy models for the brain service."""
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import uuid
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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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Column, String, Text, Integer, Float, DateTime, ForeignKey, Index, text
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)
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from sqlalchemy.dialects.postgresql import JSONB, UUID, ARRAY
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from sqlalchemy.orm import relationship
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from app.config import OPENAI_EMBED_DIM
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from app.database import Base
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def new_id():
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return str(uuid.uuid4())
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class Item(Base):
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__tablename__ = "items"
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id = Column(UUID(as_uuid=False), primary_key=True, default=new_id)
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user_id = Column(String(64), nullable=False, index=True)
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type = Column(String(32), nullable=False, default="link") # link|note|pdf|image|document|file
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title = Column(Text, nullable=True)
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url = Column(Text, nullable=True)
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raw_content = Column(Text, nullable=True) # original user input (note body, etc.)
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extracted_text = Column(Text, nullable=True) # full extracted text from page/doc
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folder_id = Column(UUID(as_uuid=False), ForeignKey("folders.id", ondelete="SET NULL"), nullable=True)
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folder = Column(String(64), nullable=True) # denormalized folder name for fast reads
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tags = Column(ARRAY(String), nullable=True, default=list) # denormalized tag names for fast reads
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summary = Column(Text, nullable=True)
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confidence = Column(Float, nullable=True)
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metadata_json = Column(JSONB, nullable=True, default=dict)
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processing_status = Column(String(32), nullable=False, default="pending") # pending|processing|ready|failed
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processing_error = Column(Text, nullable=True)
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# Embedding (pgvector)
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embedding = Column(Vector(OPENAI_EMBED_DIM), nullable=True)
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created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
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updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False)
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# Relationships
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assets = relationship("ItemAsset", back_populates="item", cascade="all, delete-orphan")
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additions = relationship(
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"ItemAddition",
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back_populates="item",
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cascade="all, delete-orphan",
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order_by="ItemAddition.created_at",
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)
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__table_args__ = (
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Index("ix_items_user_status", "user_id", "processing_status"),
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Index("ix_items_user_folder", "user_id", "folder"),
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Index("ix_items_created", "created_at"),
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)
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class ItemAsset(Base):
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__tablename__ = "item_assets"
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id = Column(UUID(as_uuid=False), primary_key=True, default=new_id)
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item_id = Column(UUID(as_uuid=False), ForeignKey("items.id", ondelete="CASCADE"), nullable=False, index=True)
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asset_type = Column(String(32), nullable=False) # screenshot|archived_html|original_upload|extracted_file
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filename = Column(String(512), nullable=False)
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content_type = Column(String(128), nullable=True)
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size_bytes = Column(Integer, nullable=True)
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storage_path = Column(String(1024), nullable=False) # relative path in storage
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created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
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# Relationships
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item = relationship("Item", back_populates="assets")
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class AppLink(Base):
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"""Placeholder for future cross-app linking (e.g. link a saved item to a trip or task)."""
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__tablename__ = "app_links"
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id = Column(UUID(as_uuid=False), primary_key=True, default=new_id)
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item_id = Column(UUID(as_uuid=False), ForeignKey("items.id", ondelete="CASCADE"), nullable=False, index=True)
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app = Column(String(64), nullable=False) # trips|tasks|fitness|inventory
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app_entity_id = Column(String(128), nullable=False)
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created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
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class ItemAddition(Base):
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__tablename__ = "item_additions"
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id = Column(UUID(as_uuid=False), primary_key=True, default=new_id)
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item_id = Column(UUID(as_uuid=False), ForeignKey("items.id", ondelete="CASCADE"), nullable=False, index=True)
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user_id = Column(String(64), nullable=False, index=True)
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source = Column(String(32), nullable=False, default="assistant") # assistant|manual
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kind = Column(String(32), nullable=False, default="append") # append
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content = Column(Text, nullable=False)
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metadata_json = Column(JSONB, nullable=True, default=dict)
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created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
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updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False)
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item = relationship("Item", back_populates="additions")
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