14ba3e8829
<!-- .github/pull_request_template.md --> ## Description Attempt at making incremental loading run async ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin.
54 lines
2 KiB
Python
54 lines
2 KiB
Python
from datetime import datetime, timezone
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from uuid import uuid4
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from sqlalchemy import UUID, Column, DateTime, String, JSON, Integer
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from sqlalchemy.ext.mutable import MutableDict
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from sqlalchemy.orm import relationship
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from cognee.infrastructure.databases.relational import Base
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from .DatasetData import DatasetData
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class Data(Base):
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__tablename__ = "data"
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id = Column(UUID, primary_key=True, default=uuid4)
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name = Column(String)
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extension = Column(String)
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mime_type = Column(String)
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raw_data_location = Column(String)
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owner_id = Column(UUID, index=True)
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tenant_id = Column(UUID, index=True, nullable=True)
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content_hash = Column(String)
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external_metadata = Column(JSON)
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# Store NodeSet as JSON list of strings
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node_set = Column(JSON, nullable=True)
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# MutableDict allows SQLAlchemy to notice key-value pair changes, without it changing a value for a key
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# wouldn't be noticed when commiting a database session
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pipeline_status = Column(MutableDict.as_mutable(JSON))
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token_count = Column(Integer)
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data_size = Column(Integer, nullable=True) # File size in bytes
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created_at = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))
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updated_at = Column(DateTime(timezone=True), onupdate=lambda: datetime.now(timezone.utc))
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datasets = relationship(
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"Dataset",
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secondary=DatasetData.__tablename__,
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back_populates="data",
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lazy="noload",
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cascade="all, delete",
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)
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def to_json(self) -> dict:
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return {
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"id": str(self.id),
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"name": self.name,
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"extension": self.extension,
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"mimeType": self.mime_type,
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"rawDataLocation": self.raw_data_location,
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"createdAt": self.created_at.isoformat(),
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"updatedAt": self.updated_at.isoformat() if self.updated_at else None,
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"nodeSet": self.node_set,
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# "datasets": [dataset.to_json() for dataset in self.datasets]
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}
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