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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with PostgreSQL Vector Search Extension
# =================================================================================================
# This is a production-ready starter boilerplate for building micro-SaaS applications using FastAPI and Pydantic v2.
# It includes a PostgreSQL Vector Search Extension for efficient searching and filtering of data.

from fastapi import FastAPI, Depends
from fastapi.responses import JSONResponse
from pydantic import BaseModel, Field
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session
from sqlalchemy.exc import SQLAlchemyError
from typing import List, Optional
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@host:port/dbname"

# Create the database engine
engine = create_engine(DATABASE_URL)

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

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

# Define the user model
class User(Base):
    __

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