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```python
# AI Dev Tool: Vector Search API Integration Wrapper
# ================================================
# A production-ready API integration wrapper for PostgreSQL Vector Search Extension
# Using FastAPI and Rust WebAssembly Edge Function for high-performance vector search

from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
from fastapi.requests import Request
from pydantic import BaseModel
import psycopg2
import psycopg2.extras
import json
from typing import List, Dict

# Define the PostgreSQL Vector Search Extension connection parameters
POSTGRES_HOST = "localhost"
POSTGRES_PORT = 5432
POSTGRES_DB = "vector_search_db"
POSTGRES_USER = "vector_search_user"
POSTGRES_PASSWORD = "vector_search_password"

# Define the Rust WebAssembly Edge Function endpoint
EDGE_FUNCTION_ENDPOINT = "https://example.com/edge-function"

# Create a FastAPI application instance
app = FastAPI()

# Define a Pydantic model for vector search queries
class VectorSearchQuery(BaseModel):
    """Vector search query model"""
    query_vector: List[float]
    limit: int = 10

# Define a Pydantic model for vector search results
class VectorSearchResult(BaseModel):
    """Vector search result model"""
    id:

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