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

import os
import json
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from typing import List, Optional
import psycopg2
from psycopg2 import Error

# Define the PostgreSQL connection parameters
POSTGRES_HOST = os.environ.get('POSTGRES_HOST', 'localhost')
POSTGRES_PORT = os.environ.get('POSTGRES_PORT', 5432)
POSTGRES_DB = os.environ.get('POSTGRES_DB', 'vector_search_db')
POSTGRES_USER = os.environ.get('POSTGRES_USER', 'vector_search_user')
POSTGRES_PASSWORD = os.environ.get('POSTGRES_PASSWORD', 'vector_search_password')

# Define the FastAPI app
app = FastAPI()

# Define the data model for vector search queries
class VectorSearchQuery(BaseModel):
    query_vector: List[float]
    limit: Optional[int] = 10

# Define the data model for search results
class SearchResult(BaseModel):
    id: int
    vector: List[float]
    distance: float

# Establish a connection to the PostgreSQL

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