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```python
# AI Dev Tool: Vector Search API with PostgreSQL and Rust SIMD
# =====================================================================
# This is a production-ready API integration wrapper for vector search
# using PostgreSQL and Rust SIMD. It provides a high-performance and
# scalable solution for searching large datasets.

import os
import json
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from rust_simd import vector_search

# Define the API app
app = FastAPI()

# Define the database connection
SQLALCHEMY_DATABASE_URL = os.environ.get("DATABASE_URL")
engine = create_engine(SQLALCHEMY_DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Define the vector search model
class VectorSearchModel(BaseModel):
    """Vector search model"""
    query: str
    vectors: list[float]

# Define the API endpoint for vector search
@app.post("/vector_search")
async def vector_search_endpoint(model: VectorSearchModel):
    """
    Vector search endpoint

Args:
    model (VectorSearchModel): The vector search model

Returns:
    JSONResponse: The search results
    """

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