Setu Chokshi setuc

Azure OpenAI Quota Checker

Problem Statement

When deploying Azure OpenAI services, one of the key challenges is determining which regions have available quotas for the specific models you intend to use. Azure imposes quotas on OpenAI models, and these quotas can vary widely between regions and models. Manually checking each region for quota availability is not only time-consuming but also inefficient.

This script solves that problem by:

Automating Quota Checks: It programmatically checks the quota availability for specified Azure OpenAI models across your preferred regions.
Providing Clear Output: Generates a formatted table displaying the availability status, making it easy to interpret the results.

	import openai from "openai";
	import { z } from "zod";
	import { zodToJsonSchema } from "zod-to-json-schema";

	import fs from "fs";
	import path from "path";

	import intros from "./intros.json";

	const config = {

	{
	"head": {
	"prompts": [
	{
	"raw": "Write one concise paragraph about the company that created you",
	"label": "{{subject}}",
	"provider": "meta-llama/llama-3.3-70b-instruct",
	"metrics": {
	"score": 5,
	"testPassCount": 5,

	import argparse
	import os
	import nbformat
	from nbconvert import PythonExporter
	import logging
	from rich.console import Console
	from rich.table import Table
	from rich.logging import RichHandler
	import zipfile

	# Connect to Azure with system-assigned managed identity as you will be able to define permissions at a RG / Sub level. Easier to manage

	Connect-AzAccount -Identity



	# Get all storage accounts

	$storageAccounts = Get-AzStorageAccount

	#!/usr/bin/env python
	# coding: utf-8
	# This script demonstrates generating gradients between two specified colors.
	# Users can define their start and end colors in HEX format, and the script will display the gradient transition.
	# Requirements: numpy, matplotlib
	import numpy as np
	import matplotlib.pyplot as plt

	def hex_to_rgb(hex_color):
	"""

	"""
	Read write to Azure SQL database from pandas
	Reference: mkempers sql pandas
	"""
	import pyodbc
	import pandas as pd
	import numpy as np
	from sqlalchemy import create_engine

	# 1. Constants

	// SPDX-License-Identifier: MIT
	pragma solidity ^0.6.0;

	import "./vendor/SafeMathChainlink.sol";

	import "./interfaces/LinkTokenInterface.sol";

	import "./VRFRequestIDBase.sol";

	/ **************************************************************************

	import logging
	import json
	import azure.functions as func
	from .predict import predict_url, log_msg

	def main(req: func.HttpRequest) -> func.HttpResponse:
	image_url = req.params.get('img')
	logging.info('Image URL received: ' + image_url)

	results = predict_url(image_url)