⚡ Live Sandbox: AI Dev Tool: PostgreSQL Vector Search (07eb)

📝 Editable Code Sandbox

```python
# AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate with PostgreSQL Vector Search Extension
# =================================================================================================
# This is a high-demand, production-ready developer code asset for building micro-SaaS applications
# using FastAPI, Pydantic v2, and PostgreSQL Vector Search Extension.

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional
import psycopg2
from psycopg2 import Error
from psycopg2.extras import DictCursor
import logging

# Initialize the FastAPI application
app = FastAPI()

# Define the Pydantic model for the data
class Data(BaseModel):
    id: int
    name: str
    description: Optional[str]

# Define the PostgreSQL database connection settings
DB_HOST = "localhost"
DB_NAME = "mydatabase"
DB_USER = "myuser"
DB_PASSWORD = "mypassword"

# Create a logger
logger = logging.getLogger(__name__)

# Define a function to connect to the PostgreSQL database
def connect_to_db():
    try:
        conn = psycopg2.connect(
            host=DB_HOST,
            database=DB_NAME,
            user=DB_USER,
            password=DB_PASSWORD,
            cursor_factory=DictCursor

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