knowledge-agent/database/models.py

from sqlalchemy import Column, Integer, String, DateTime, Text, BigInteger
from datetime import datetime
from .db import Base


class KnowledgeParsingContent(Base):
    __tablename__ = 'knowledge_parsing_content'
    
    id = Column(BigInteger, primary_key=True, autoincrement=True)
    content_id = Column(String(128), nullable=False)
    request_id = Column(String(128), nullable=False)
    task_id = Column(BigInteger, nullable=False)
    parsing_data = Column(Text, comment='结构化数据')
    create_time = Column(DateTime, default=datetime.now)
    status = Column(Integer, default=0, comment='0: 未开始，1:处理中 2: 处理完成 3:处理失败')
    indentify_data = Column(Text, comment='理解的数据')
    
    def __repr__(self):
        return f"<KnowledgeParsingContent(id={self.id}, content_id={self.content_id}, status={self.status})>"

class KnowledgeExtractionContent(Base):
    __tablename__ = 'knowledge_extraction_content'
    
    id = Column(BigInteger, primary_key=True, autoincrement=True)
    request_id = Column(String(128), nullable=False)
    parsing_id = Column(BigInteger, nullable=False)
    score = Column(Integer, default=-1)
    score_reason = Column(Text, comment='打分原因')
    data = Column(Text, comment='结构化数据')
    clean_reason = Column(Text, comment='清洗原因')
    create_at = Column(DateTime, default=datetime.now)
    status = Column(Integer, default=0, comment='0: 未开始，1:处理中 2: 处理完成 3:处理失败')
    
    def __repr__(self):
        return f"<KnowledgeExtractionContent(id={self.id}, request_id={self.request_id}, status={self.status})>"