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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS PostgreSQL Vector Search Extension
# Description: A production-ready FastAPI boilerplate with PostgreSQL vector search extension
# Author: Elite Software Architect and Micro-SaaS Developer

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 FastAPI app
app = FastAPI()

# Define the PostgreSQL database connection
POSTGRES_USER = "your_username"
POSTGRES_PASSWORD = "your_password"
POSTGRES_HOST = "your_host"
POSTGRES_PORT = "your_port"
POSTGRES_DB = "your_database"

# Create a PostgreSQL database engine
engine = create_engine(f"postgresql://{POSTGRES_USER}:{POSTGRES_PASSWORD}@{POSTGRES_HOST}:{POSTGRES_PORT}/{POSTGRES_DB}")

# Create a configured "Session" class
Session = sessionmaker(bind=engine)

# Create a base class for declar

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