model/contextual_response/database.py

from sqlalchemy import create_engine, Column, String, Integer, JSON, ARRAY, Float
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Get database URL from environment variable
DATABASE_URL="postgresql://ai_5zls_user:wDwKj39nM2whJRHy7J2OgDRWl53w5GUG@dpg-cuifsvin91rc73bhvch0-a.oregon-postgres.render.com/ai_5zls"

# Create SQLAlchemy engine
engine = create_engine(DATABASE_URL)

# Create session factory
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Create base class for declarative models
Base = declarative_base()

class DocumentEmbedding(Base):
    """Model for storing document embeddings."""
    __tablename__ = "document_embeddings"

    id = Column(Integer, primary_key=True, index=True)
    content = Column(String, index=True)
    embedding = Column(ARRAY(Float))
    doc_metadata = Column(JSON)
    source = Column(String, index=True)