🔥 Trending Repository: Cloud-DevOps-Learning-Resources
📝 Description: This repo includes Books and imp notes related to GCP, Azure, AWS, Docker, K8s, and DevOps. More, exam and interview prep notes.
🔗 Repository URL: https://github.com/ahmedtariq01/Cloud-DevOps-Learning-Resources
📖 Readme: https://github.com/ahmedtariq01/Cloud-DevOps-Learning-Resources#readme
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==================================
🧠 By: https://t.iss.one/DataScienceN
  📝 Description: This repo includes Books and imp notes related to GCP, Azure, AWS, Docker, K8s, and DevOps. More, exam and interview prep notes.
🔗 Repository URL: https://github.com/ahmedtariq01/Cloud-DevOps-Learning-Resources
📖 Readme: https://github.com/ahmedtariq01/Cloud-DevOps-Learning-Resources#readme
📊 Statistics:
🌟 Stars: 1.7K stars
👀 Watchers: 38
🍴 Forks: 539 forks
💻 Programming Languages: Not available
🏷️ Related Topics:
#linux #docker #kubernetes #jenkins #aws #ansible #devops #notes #azure #containers #terraform #gcp #cicd #devops_tools #cloudnative #cloudsecurity #cloudcomputing #devsecops #multicloud #azure_devops
==================================
🧠 By: https://t.iss.one/DataScienceN
Forwarded from Data Science Machine Learning Data Analysis
In Python, building AI-powered Telegram bots unlocks massive potential for image generation, processing, and automation—master this to create viral tools and ace full-stack interviews! 🤖
Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots
https://t.iss.one/DataScienceM🦾 
# Basic Bot Setup - The foundation (PTB v20+ Async)
from telegram.ext import Application, CommandHandler, MessageHandler, filters
async def start(update, context):
await update.message.reply_text(
"✨ AI Image Bot Active!\n"
"/generate - Create images from text\n"
"/enhance - Improve photo quality\n"
"/help - Full command list"
)
app = Application.builder().token("YOUR_BOT_TOKEN").build()
app.add_handler(CommandHandler("start", start))
app.run_polling()
# Image Generation - DALL-E Integration (OpenAI)
import openai
from telegram.ext import ContextTypes
openai.api_key = os.getenv("OPENAI_API_KEY")
async def generate(update: Update, context: ContextTypes.DEFAULT_TYPE):
if not context.args:
await update.message.reply_text("❌ Usage: /generate cute robot astronaut")
return
prompt = " ".join(context.args)
try:
response = openai.Image.create(
prompt=prompt,
n=1,
size="1024x1024"
)
await update.message.reply_photo(
photo=response['data'][0]['url'],
caption=f"🎨 Generated: *{prompt}*",
parse_mode="Markdown"
)
except Exception as e:
await update.message.reply_text(f"🔥 Error: {str(e)}")
app.add_handler(CommandHandler("generate", generate))
Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots
#Python #TelegramBot #AI #ImageGeneration #StableDiffusion #OpenAI #MachineLearning #CodingInterview #FullStack #Chatbots #DeepLearning #ComputerVision #Programming #TechJobs #DeveloperTips #CareerGrowth #CloudComputing #Docker #APIs #Python3 #Productivity #TechTips
https://t.iss.one/DataScienceM
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