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```python
# AI Dev Tool: Gravitational Vector Search API Integration Wrapper
# Description: A high-performance API integration wrapper for PostgreSQL Vector Search Extension
# Author: Elite Software Architect and Micro-SaaS Developer

import os
import logging
from typing import Dict, List
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
from pydantic import BaseModel
import psycopg2
from psycopg2 import Error
from psycopg2.extras import DictCursor

# Initialize the FastAPI application
app = FastAPI()

# Define the PostgreSQL connection parameters
POSTGRES_HOST = os.environ.get('POSTGRES_HOST')
POSTGRES_DB = os.environ.get('POSTGRES_DB')
POSTGRES_USER = os.environ.get('POSTGRES_USER')
POSTGRES_PASSWORD = os.environ.get('POSTGRES_PASSWORD')

# Define the Vector Search API endpoint
class VectorSearchRequest(BaseModel):
    """Vector Search Request Model"""
    query: str
    limit: int = 10

class VectorSearchResponse(BaseModel):
    """Vector Search Response Model"""
    results: List[Dict]

# Define the PostgreSQL Vector Search Extension query function
def query_vector_search(query: str, limit: int = 10) -> List[Dict]:
    """

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