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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate for Secondhand Book Sales
# ==============================================================================
# This is a production-ready boilerplate for building a FastAPI Pydantic v2 Micro-SaaS
# application for secondhand book sales. It includes PostgreSQL Vector Search Extension
# for efficient book search and AI-powered book recommendation.

from fastapi import FastAPI, Depends
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
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
import psycopg2
import aiopg

# Initialize FastAPI application
app = FastAPI()

# Initialize 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)

Base = declarative_base()

# Define book model
class Book(Base):
    __tablename__ = "books"
    id = Column(Integer, primary_key=True)
    title = Column(String)
    author =

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