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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with PostgreSQL Vector Search
# ==============================================================================
# This is a production-ready starter boilerplate for building micro-SaaS applications
# using FastAPI, Pydantic v2, and PostgreSQL Vector Search.

from fastapi import FastAPI, Depends, HTTPException
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
from pydantic import BaseModel
from typing import List, Optional
from psycopg2 import connect, Error
from psycopg2.extras import DictCursor
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session

# Initialize FastAPI app
app = FastAPI()

# Initialize PostgreSQL connection
POSTGRES_HOST = "localhost"
POSTGRES_DB = "mydb"
POSTGRES_USER = "myuser"
POSTGRES_PASSWORD = "mypassword"

# Create a PostgreSQL connection engine
engine = create_engine(f"postgresql://{POSTGRES_USER}:{POSTGRES_PASSWORD}@{POSTGRES_HOST}/{POSTGRES_DB}")

# Create a configured "Session" class
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Create

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