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```python
# AI Dev Tool: PostgreSQL Vector Search Extension Boilerplate
# Description: A production-ready starter boilerplate for building scalable vector search applications with PostgreSQL

import os
import psycopg2
from psycopg2 import Error
from typing import List, Tuple

# PostgreSQL connection settings
PG_HOST = os.environ.get('PG_HOST', 'localhost')
PG_DATABASE = os.environ.get('PG_DATABASE', 'vector_search')
PG_USER = os.environ.get('PG_USER', 'postgres')
PG_PASSWORD = os.environ.get('PG_PASSWORD', 'postgres')

# Create a PostgreSQL connection
def create_connection() -> psycopg2.Connection:
    """Create a connection to the PostgreSQL database"""
    try:
        connection = psycopg2.connect(
            host=PG_HOST,
            database=PG_DATABASE,
            user=PG_USER,
            password=PG_PASSWORD
        )
        return connection
    except Error as e:
        print(f"Error creating connection: {e}")
        return None

# Create a vector search table
def create_vector_search_table(connection: psycopg2.Connection, table_name: str) -> bool:
    """Create a vector search table with the given name"""
    try:
        cursor = connection.cursor()
        cursor.execute(f"""
            CREATE TABLE IF NOT EXISTS {

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