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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Starter
# ================================================
# A production-ready starter boilerplate for building micro-SaaS applications
# using FastAPI, Pydantic v2, and PostgreSQL Vector Search Extension.

from fastapi import FastAPI, Depends
from fastapi.responses import JSONResponse
from pydantic import BaseModel, Field
from typing import Optional
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session
import psycopg2
import json

# Initialize the FastAPI application
app = FastAPI()

# Define the PostgreSQL database connection
SQLALCHEMY_DATABASE_URL = "postgresql://user:password@host:port/dbname"
engine = create_engine(SQLALCHEMY_DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Define the base class for SQLAlchemy models
Base = declarative_base()

# Define the User model
class User(Base):
    __tablename__ = "users"
    id = Column(Integer, primary_key=True)
    name = Column(String)
    email = Column(String, unique=True)

# Create the database tables
Base.metadata.create

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