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from sqlalchemy import (
BigInteger,
Column,
DateTime,
ForeignKey,
JSON,
String,
Text,
Integer,
Boolean,
Enum as SQLAlchemyEnum,
)
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base
from datetime import datetime
from .process_status import ProcessStatus
from .dto.chunk_dto import ChunkDTO
Base = declarative_base()
class ChunkModel(Base):
__tablename__ = "chunk"
id = Column(BigInteger, primary_key=True)
document_id = Column(BigInteger, ForeignKey("document.id"), nullable=False)
content = Column(Text, nullable=False)
has_embedding = Column(Boolean, default=False)
tags = Column(JSON)
topic = Column(String(255))
create_time = Column(DateTime, default=datetime.utcnow)
document = relationship("DocumentModel", back_populates="chunks")
def to_dto(self) -> ChunkDTO:
return ChunkDTO(
id=self.id,
document_id=self.document_id,
content=self.content,
has_embedding=self.has_embedding, # ensure this field is correctly converted
tags=self.tags,
topic=self.topic,
length=len(self.content) if self.content else 0,
)
class DocumentModel(Base):
__tablename__ = "document"
id = Column(Integer, primary_key=True, autoincrement=True)
name = Column(String(255), nullable=False)
title = Column(String(255))
mime_type = Column(String(100))
user_description = Column(Text)
url = Column(String(1024))
document_size = Column(Integer, default=0)
raw_content = Column(Text)
insight = Column(JSON)
summary = Column(JSON)
keywords = Column(JSON)
extract_status = Column(
SQLAlchemyEnum(ProcessStatus), default=ProcessStatus.INITIALIZED
)
embedding_status = Column(
SQLAlchemyEnum(ProcessStatus), default=ProcessStatus.INITIALIZED
)
create_time = Column(DateTime, default=datetime.now)
update_time = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
chunks = relationship(
"ChunkModel", back_populates="document", cascade="all, delete-orphan"
)
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