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51 lines
2.1 KiB
Python
51 lines
2.1 KiB
Python
import sqlalchemy
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from .base import Base
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# Base = declarative_base()
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# DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///./rag_knowledge.db')
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# print("Using database URL:", DATABASE_URL)
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# engine = create_engine(DATABASE_URL, connect_args={'check_same_thread': False})
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# SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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# def create_db_and_tables():
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# """Creates all database tables defined in the Base."""
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# Base.metadata.create_all(bind=engine)
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# print('Database tables created or already exist.')
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class KnowledgeBase(Base):
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__tablename__ = 'knowledge_bases'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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name = sqlalchemy.Column(sqlalchemy.String, index=True)
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description = sqlalchemy.Column(sqlalchemy.Text)
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created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
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embedding_model_uuid = sqlalchemy.Column(sqlalchemy.String, default='')
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top_k = sqlalchemy.Column(sqlalchemy.Integer, default=5)
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class File(Base):
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__tablename__ = 'knowledge_base_files'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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kb_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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file_name = sqlalchemy.Column(sqlalchemy.String)
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extension = sqlalchemy.Column(sqlalchemy.String)
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created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
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status = sqlalchemy.Column(sqlalchemy.String, default='pending') # pending, processing, completed, failed
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class Chunk(Base):
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__tablename__ = 'knowledge_base_chunks'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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file_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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text = sqlalchemy.Column(sqlalchemy.Text)
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# class Vector(Base):
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# __tablename__ = 'knowledge_base_vectors'
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# uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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# chunk_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
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# embedding = sqlalchemy.Column(sqlalchemy.LargeBinary)
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