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```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Template with PostgreSQL Vector Search Extension
# ==============================================================================
# This is a high-demand production-ready developer code asset.
# It combines the power of FastAPI, Pydantic v2, and PostgreSQL Vector Search Extension
# to create a robust Micro-SaaS template.

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

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

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

# Define a model for vector search
class VectorSearchModel(Base):
    __tablename__ = "vector_search"
    id = Column(Integer, primary_key

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