si3mshady

from pathlib import Path
import sys,os
import tempfile
from autogen import ConversableAgent
from autogen.coding import DockerCommandLineCodeExecutor

# python3 -m venv pyautogen
# source pyautogen/bin/activate
# pip install pyautogen

si3mshady

name: Install Docker on CentOS

on:
  push:
    branches:
      - main

jobs:

  install-docker:

si3mshady

import React, { useState, useEffect, useRef } from 'react';
// import ReactDOM from 'react-dom';
import  trinity from './trinity.mp4'
import './App.css';

function App() {
  const maxRetryCount = 3;
  const maxDelaySec = 4;

  const REACT_APP_INIT_SCRIPT = process.env.REACT_APP_INIT_SCRIPT || "Hey Elliott, what are we going to work on today? Wait, why do I even need to ask I already know it will be fun";

si3mshady

import json

arrangement_packages = [
    {
        "id": 1,
        "name": "Fruit Symphony",
        "description": "Immerse yourself in the harmonious blend of nature's finest fruits with our Fruit Symphony arrangement. Picture a grand orchestra of flavors, where succulent strawberries, ripe mangoes, tangy pineapples, and crisp apples come together in perfect unison. Each bite is a symphony of taste, a crescendo of sweetness and freshness that delights the senses. Whether you're hosting a garden party, a summer soirée, or simply indulging in a moment of pure bliss, let the Fruit Symphony arrangement be your conductor to culinary euphoria.",
        "price": 39.99
    },
    {

si3mshady

provider "aws" {
  region = "us-east-1"
}

# Create VPC
resource "aws_vpc" "my_vpc" {
  cidr_block = "10.0.0.0/16"
}

# Create Subnets

si3mshady

from flask import Flask, request, jsonify
import json
import boto3

app = Flask(__name__)

brt = boto3.client(service_name='bedrock-runtime')

@app.route('/invoke_claude', methods=['POST'])
def invoke_claude():

si3mshady

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: minio-storage-class
provisioner: kubernetes.io/gce-pd # or the appropriate provisioner for your cluster
volumeBindingMode: Immediate



---

si3mshady

#!/bin/bash

# Install Python and create a virtual environment
sudo apt-get update -y
sudo apt-get install -y python3.11 python3.11-venv

# Create and activate virtual environment
python3.11 -m venv venv
source venv/bin/activate

si3mshady

from typing import Optional, List, Mapping, Any
import requests 
from llama_index.core import SimpleDirectoryReader, SummaryIndex
from llama_index.core.callbacks import CallbackManager
from llama_index.core.llms import (
    CustomLLM,
    CompletionResponse,
    CompletionResponseGen,
    LLMMetadata,
)

si3mshady

offensive_conversations = [
    {"sexism": "Women should stay in the kitchen where they belong."},
    {"misogyny": "I can't stand women; they're all just objects for men's pleasure."},
    {"homophobia": "I don't want any gays around me; they're disgusting."},
    {"xenophobia": "Those immigrants are stealing our jobs and ruining our country."},
    {"obscenity": "That movie was so obscene; it should be banned."},
    {"vulgarity": "She's so vulgar; I can't believe she talks like that."},
    {"discrimination": "We don't hire people with foreign-sounding names; they're all trouble."},
    {"hate crime": "Those people got what they deserved for being different; it's not a hate crime."},
    {"bigotry": "I hate everyone who doesn't look like me; it's called being patriotic."},