66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
from sqlalchemy import Column, DateTime, String, create_engine, Boolean, Text
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from sqlalchemy.orm import declarative_base, sessionmaker
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# 申明基类对象
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Base = declarative_base()
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from decouple import config
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DB_PATH = config('DB_PATH', default='E://pyptoject//sqlbot_agent//main.sqlite3')
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class QuestionFeedBack(Base):
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# 定义表名
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__tablename__ = 'db_question_feedback'
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__table_args__ = {'extend_existing': True}
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# 定义字段
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id = Column(String(255), primary_key=True)
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create_time = Column(DateTime, nullable=False, )
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question = Column(String(255), nullable=False)
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sql = Column(String(500), nullable=False)
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user_id = Column(String(100), nullable=False, default='1')
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# 用户意见反馈
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user_comment = Column(Text, nullable=True)
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# 用户点赞，点踩
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user_praise = Column(Boolean, nullable=False, default=False)
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# 该数据是否被认为梳理过
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is_process = Column(Boolean, nullable=False, default=False)
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class Conversation(Base):
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__tablename__ = 'db_conversation'
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id = Column(String(255), primary_key=True)
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create_time = Column(DateTime, nullable=False, )
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question = Column(String(500), nullable=False)
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sql = Column(String(500), nullable=True)
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user_id = Column(String(100), nullable=False)
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cvs_id = Column(String(100), nullable=False)
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meta = Column(Text, nullable=True)
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class PredefinedQuestion(Base):
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# 定义表名,预制问题表
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__tablename__ = 'db_predefined_question'
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__table_args__ = {'extend_existing': True}
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# 定义字段
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id = Column(String(255), primary_key=True)
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question = Column(String(255), nullable=False)
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user_id = Column(String(100), nullable=False, default='1')
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# 该数据是否被认为梳理过
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enable = Column(Boolean, nullable=False, default=True)
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def to_dict(self):
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return {c.name: getattr(self, c.name) for c in self.__table__.columns}
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class SqliteSqlalchemy(object):
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def __init__(self):
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# 创建sqlite连接引擎
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engine = create_engine(f'sqlite:///{DB_PATH}', echo=True)
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# 创建表
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Base.metadata.create_all(engine, checkfirst=True)
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# 创建sqlite的session连接对象
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self.session = sessionmaker(bind=engine)()
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