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```python
# AI Dev Tool: Vector Search API
# Description: A production-ready API integration wrapper for PostgreSQL Vector Search Extension
# Category: API Integration Wrapper

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional
import psycopg2
from psycopg2 import Error
from psycopg2.extras import DictCursor
import logging

# Initialize the logger
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Define the FastAPI app
app = FastAPI()

# Define the database connection settings
DB_HOST = "localhost"
DB_NAME = "vector_search_db"
DB_USER = "vector_search_user"
DB_PASSWORD = "vector_search_password"

# Define the PostgreSQL Vector Search Extension connection
def get_db_connection():
    try:
        connection = psycopg2.connect(
            host=DB_HOST,
            database=DB_NAME,
            user=DB_USER,
            password=DB_PASSWORD,
            cursor_factory=DictCursor
        )
        return connection
    except Error as e:
        logger.error(f"Failed to connect to database: {e}")
        raise HTTPException(status_code=500, detail="Failed to connect to database")

# Define the vector search model
class VectorSearchModel(BaseModel):

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