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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with PostgreSQL Vector Search Extension
# ==================================================================================================
from fastapi import FastAPI, Depends
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from typing import List, Optional
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session
from sqlalchemy.exc import SQLAlchemyError
from psycopg2.extras import Json

# Initialize FastAPI application
app = FastAPI(title="FastAPI Pydantic v2 Micro-SaaS Boilerplate",
              description="A production-ready starter boilerplate with PostgreSQL vector search extension",
              version="1.0.0")

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

# Create database engine
engine = create_engine(SQLALCHEMY_DATABASE_URL)

# Create session maker
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Create base class for models
Base = declarative_base()

# Define a model for vector search
class VectorSearchModel(Base):
    __tablename__ = "vector_search"

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