⚡ Live Sandbox: AI Dev Tool: vLLM v0280

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```python
# AI Dev Tool: Secure Vector Search API
# =======================================
# A production-ready API integration wrapper for secure vector search using PostgreSQL Vector Search Extension and FastAPI Pydantic v2

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
import logging

# Initialize the logger
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Define the PostgreSQL connection parameters
POSTGRES_HOST = "localhost"
POSTGRES_DB = "vector_search"
POSTGRES_USER = "postgres"
POSTGRES_PASSWORD = "postgres"

# Define the FastAPI app
app = FastAPI()

# Define the Pydantic model for vector search queries
class VectorSearchQuery(BaseModel):
    query: str
    limit: Optional[int] = 10

# Define the Pydantic model for vector search results
class VectorSearchResult(BaseModel):
    id: int
    vector: List[float]
    score: float

# Establish a connection to the PostgreSQL database
def connect_to_db():
    try:
        conn = psycopg2.connect(
            host=POSTGRES_HOST,
            database=POST

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