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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with PostgreSQL Vector Search Extension
# ==================================================================================================
# This is a high-demand production starter boilerplate for building micro-SaaS applications
# using FastAPI, Pydantic v2, and PostgreSQL Vector Search Extension.

from fastapi import FastAPI, Depends
from fastapi.responses import JSONResponse
from pydantic import BaseModel
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
import psycopg2
import uvicorn

# Initialize the FastAPI application
app = FastAPI()

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

# Create a PostgreSQL database engine
engine = create_engine(DATABASE_URL)

# Create a configured "Session" class
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

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

# Define the User model
class User(Base):
    """User model"""
    __tablename__ =

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