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```python
# AI Dev Tool: Vector Search API
# A high-demand, production-ready developer code asset
# Category: API Integration Wrapper
# Description: PostgreSQL Vector Search Extension API wrapper using FastAPI and Pydantic

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional
import psycopg2
from psycopg2 import Error

# PostgreSQL connection settings
POSTGRES_HOST = "localhost"
POSTGRES_DB = "vector_search_db"
POSTGRES_USER = "vector_search_user"
POSTGRES_PASSWORD = "vector_search_password"

# Create a FastAPI app
app = FastAPI()

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

# Define a Pydantic model for search results
class SearchResult(BaseModel):
    """Search result model"""
    id: int
    vector: List[float]
    distance: float

# Create a PostgreSQL connection pool
def create_connection():
    """Create a PostgreSQL connection"""
    try:
        connection = psycopg2.connect(
            host=POSTGRES_HOST,
            database=POSTGRES_DB,

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