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```python
# AI Dev Tool: Turbocharged PostgreSQL Vector Search Extension
# =============================================================
# This code asset provides a production-ready API Integration Wrapper 
# for the PostgreSQL Vector Search Extension, utilizing the principles 
# of fast Tokio applications and Cloudflare AKE for optimized performance.

import os
import psycopg2
from psycopg2 import extras
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional

# Define the VectorSearchRequest model
class VectorSearchRequest(BaseModel):
    """Request model for vector search"""
    query_vector: List[float]
    limit: Optional[int] = 10

# Define the VectorSearchResponse model
class VectorSearchResponse(BaseModel):
    """Response model for vector search"""
    results: List[dict]

# Initialize the FastAPI application
app = FastAPI()

# Define the PostgreSQL connection settings
POSTGRES_HOST = os.environ.get("POSTGRES_HOST", "localhost")
POSTGRES_PORT = os.environ.get("POSTGRES_PORT", 5432)
POSTGRES_USER = os.environ.get("POSTGRES_USER", "postgres")
POSTGRES_PASSWORD = os.environ.get("POSTGRES_PASSWORD", "postgres")
POSTGRES_DB = os.environ.get("POSTGRES_DB",

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