abhi-io

import os
from openai import OpenAI

client = OpenAI(
    api_key = os.getenv("OPENAI_API_KEY"),
)

completion = client.chat.completions.create( # Change the method
  model = "gpt-3.5-turbo",
  messages = [ # Change the prompt parameter to messages parameter

abhi-io

import React, { useEffect } from 'react';
import * as THREE from 'three';
import { GLTFLoader } from 'three/examples/jsm/loaders/GLTFLoader';
import { OrbitControls } from 'three/examples/jsm/controls/OrbitControls';

function Basic3d() {
  useEffect(() => {
    // Scene
    const scene = new THREE.Scene();
    scene.background = new THREE.Color(0xaaaaaa); // Optional: Change scene background

abhi-io

Install frappe-bench using docker

Clone frappe_docker

git clone https://github.com/frappe/frappe_docker.git
cd frappe_docker

Install bench using docker

abhi-io

# The script returns a kubeconfig for the service account given
# reff:  https://gist.github.com/innovia/fbba8259042f71db98ea8d4ad19bd708
# you need to have kubectl on PATH with the context set to the cluster you want to create the config for

# Cosmetics for the created config
clusterName=some-cluster
# your server address goes here get it via kubectl cluster-info
server=https://157.90.17.72:6443
# the Namespace and ServiceAccount name that is used for the config
namespace=kube-system

abhi-io

curl --silent --remote-name --location https://github.com/ceph/ceph/raw/octopus/src/cephadm/cephadm
sudo mv cephadm /usr/local/bin
sudo chmod +x /usr/local/bin/cephadm
sudo mkdir -p /etc/ceph

abhi-io

  Make bucket
      s3cmd mb s3://BUCKET
  Remove bucket
      s3cmd rb s3://BUCKET
  List objects or buckets
      s3cmd ls [s3://BUCKET[/PREFIX]]
  List all object in all buckets
      s3cmd la 
  Put file into bucket
      s3cmd put FILE [FILE...] s3://BUCKET[/PREFIX]

abhi-io

version: "3.5"
services:
  ceph:
    image: ceph/daemon:v5.0.8-stable-5.0-octopus-centos-8
    container_name: demo-ceph
    command: demo
    hostname: ceph-demo
    ports:
      - 5000:5000
      - 8000:8000

abhi-io

##this is in for loop for testing purpose
for i in {1..100000}; do ffmpeg -re -i VIDEO-FILE.mp4 -vcodec libx264 -vprofile baseline -g 30 -acodec aac -strict -2 -f flv rtmp://IP:1935/stone1/age2; done

abhi-io

ffmpeg -re -i VIDEO-FILE.mp4 -vcodec libx264 -vprofile baseline -g 30 -acodec aac -strict -2 -f flv rtmp://IP/key01/value01

abhi-io

docker build -t nginx-rtmp .
docker run -itd -p 1935:1935 -p 8080:80 -p 443:443 --rm nginx-rtmp