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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with PostgreSQL Vector Search Extension
# =============================================================================================
# This is a production-ready developer code asset for building high-performance 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 typing import 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@host:port/dbname"

# 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 sample model
class SampleModel(Base):
    __tablename__ = "samples"
    id = Column(Integer, primary_key=True)
    name = Column(String

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