⚡ Live Sandbox: AI Dev Tool: PostgreSQL Vector Search (mg30)

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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Starter Boilerplate
# =============================================================
# This is 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
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String
from sqlalchemy.exc import SQLAlchemyError
import psycopg2
import uvicorn

# Define the database connection URL
DATABASE_URL = "postgresql://user:password@host:port/dbname"

# Create a database engine
engine = create_engine(DATABASE_URL)

# Create a session maker
Session = sessionmaker(bind=engine)

# Create a base class for declarative models
Base = declarative_base()

# Define a sample model
class SampleModel(Base):
    """Sample model for demonstration purposes"""
    __tablename__ = "sample_table"
    id = Column(Integer, primary_key=True)
    name = Column(String)
    description = Column(String)

# Create the tables in the database
Base

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