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```python # AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS with PostgreSQL Vector Search Extension # Description: A production-ready starter boilerplate for building micro-SaaS applications with FastAPI, Pydantic v2, and PostgreSQL Vector Search Extension. from fastapi import FastAPI, Depends from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials from pydantic import BaseModel from typing import List from psycopg2 import connect from psycopg2.extras import DictCursor from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker import uvicorn import logging # Initialize the logger logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) # Define the database connection parameters DB_HOST = "localhost" DB_PORT = 5432 DB_NAME = "mydatabase" DB_USER = "myuser" DB_PASSWORD = "mypassword" # Create a PostgreSQL database engine engine = create_engine(f"postgresql://{DB_USER}:{DB_PASSWORD}@{DB_HOST}:{DB_PORT}/{DB_NAME}") # Create a configured "Session" class Session = sessionmaker(bind=engine) # Create a base class for declarative class
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