⚡ Live Sandbox: AI Dev Tool: PostgreSQL Vector Search Extension

📝 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
# scalable and efficient 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
import json

# Initialize the FastAPI application
app = FastAPI()

# Define the PostgreSQL database connection settings
POSTGRES_HOST = "localhost"
POSTGRES_DB = "mydatabase"
POSTGRES_USER = "myuser"
POSTGRES_PASSWORD = "mypassword"

# Define the Pydantic model for the vector search data
class VectorSearchData(BaseModel):
    id: int
    vector: List[float]
    metadata: Optional[str]

# Define the route for creating a new vector search index
@app.post("/create_index")
async def create_index():
    try:
        # Establish a connection to the PostgreSQL database
        conn = psycopg2.connect(
            host=POSTGRES_HOST,
            database=POSTGRES_DB,
            user=POSTGRES

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