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```python
# AI Dev Tool: PostgreSQL Vector Search Edge Function
# ================================================
# A production-ready edge function for PostgreSQL vector search integration
# using Rust WebAssembly and Cloudflare Worker

import os
import json
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
from fastapi.requests import Request
from pydantic import BaseModel
from typing import List, Optional
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy.exc import SQLAlchemyError
from psycopg2.extras import Json

# Define the PostgreSQL database connection URL
DATABASE_URL = os.environ.get("DATABASE_URL")

# Define the PostgreSQL vector search extension
VECTOR_SEARCH_EXTENSION = "pg_vector"

# Define the edge function API
app = FastAPI()

# Define the database engine and session maker
engine = create_engine(DATABASE_URL)
Session = sessionmaker(bind=engine)

# Define the base model for declarative base
Base = declarative_base()

# Define the vector search model
class VectorSearchModel(Base):
    __tablename__ = "vector_search"
    id = Column(Integer, primary_key=True)
    vector = Column(Json)

# Create

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