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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate
# =============================================
# A production-ready starter boilerplate for building micro-SaaS applications
# using FastAPI, Pydantic v2, and PostgreSQL Vector Search Extension.

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy.exc import SQLAlchemyError
import psycopg2
import logging

# Initialize the logger
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Define the database connection URL
DATABASE_URL = "postgresql://user:password@localhost:5432/database"

# Create a database engine
engine = create_engine(DATABASE_URL)

# Create a session maker
Session = sessionmaker(bind=engine)

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

# Define a Pydantic model for the user
class User(BaseModel):
    """A Pydantic model representing a user."""
    id: int
    name: str
    email: str

# Define a Pydantic

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