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```python
# AI Dev Tool: FastAPI + PostgreSQL Vector Search Extension Boilerplate
# =====================================================================
# This is a production-ready boilerplate for building fast and scalable APIs
# using FastAPI and PostgreSQL Vector Search Extension.

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

# PostgreSQL connection settings
POSTGRES_HOST = "localhost"
POSTGRES_PORT = 5432
POSTGRES_DB = "mydb"
POSTGRES_USER = "myuser"
POSTGRES_PASSWORD = "mypassword"

# Create a FastAPI app
app = FastAPI()

# Define a Pydantic model for vector search requests
class VectorSearchRequest(BaseModel):
    query: str
    limit: int = 10

# Define a Pydantic model for vector search responses
class VectorSearchResponse(BaseModel):
    results: List[dict]

# Create a PostgreSQL connection pool
def get_db_connection():
    """Get a PostgreSQL database connection."""
    try:
        return psycopg2.connect(
            host=POSTGRES_HOST,
            port=POSTGRES_PORT,

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