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```python
# AI Dev Tool: PostgreSQL Vector Search Extension Boilerplate
# ================================================
# This boilerplate provides a production-ready starter for building vector search applications
# using PostgreSQL and Python. It includes a CLI automation tool for indexing and querying vectors.

import os
import sys
import psycopg2
from psycopg2 import Error
from typing import List, Tuple
from pydantic import BaseModel

# PostgreSQL Connection Settings
class PostgreSQLConfig(BaseModel):
    """PostgreSQL connection settings"""
    host: str
    database: str
    user: str
    password: str

# Vector Search Model
class VectorSearchModel(BaseModel):
    """Vector search model"""
    id: int
    vector: List[float]

# PostgreSQL Vector Search Extension
class PostgreSQLVectorSearch:
    """PostgreSQL vector search extension"""
    def __init__(self, config: PostgreSQLConfig):
        self.config = config
        self.conn = None

def connect(self):
        """Connect to PostgreSQL database"""
        try:
            self.conn = psycopg2.connect(
                host=self.config.host,
                database=self.config.database,
                user=self.config.user,
                password=self.config.password
            )
            print("Connected to PostgreSQL database")
        except Error as e:
            print

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