π₯ Trending Repository: drawnix
π Description: εΌζΊη½ζΏε·₯ε ·οΌSaaSοΌοΌδΈδ½εη½ζΏοΌε ε«ζη»΄ε―ΌεΎγζ΅η¨εΎγθͺη±η»ηγAll in one open-source whiteboard tool with mind, flowchart, freehand and etc.
π Repository URL: https://github.com/plait-board/drawnix
π Website: https://drawnix.com
π Readme: https://github.com/plait-board/drawnix#readme
π Statistics:
π Stars: 4.6K stars
π Watchers: 16
π΄ Forks: 373 forks
π» Programming Languages: TypeScript - SCSS - HTML
π·οΈ Related Topics:
==================================
π§ By: https://t.iss.one/DataScienceM
π Description: εΌζΊη½ζΏε·₯ε ·οΌSaaSοΌοΌδΈδ½εη½ζΏοΌε ε«ζη»΄ε―ΌεΎγζ΅η¨εΎγθͺη±η»ηγAll in one open-source whiteboard tool with mind, flowchart, freehand and etc.
π Repository URL: https://github.com/plait-board/drawnix
π Website: https://drawnix.com
π Readme: https://github.com/plait-board/drawnix#readme
π Statistics:
π Stars: 4.6K stars
π Watchers: 16
π΄ Forks: 373 forks
π» Programming Languages: TypeScript - SCSS - HTML
π·οΈ Related Topics:
#productivity #drawing #collaboration #whiteboard #flowchart #mindmap #localfirst
==================================
π§ By: https://t.iss.one/DataScienceM
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π₯ Trending Repository: drawnix
π Description: εΌζΊη½ζΏε·₯ε ·οΌSaaSοΌοΌδΈδ½εη½ζΏοΌε ε«ζη»΄ε―ΌεΎγζ΅η¨εΎγθͺη±η»ηγAll in one open-source whiteboard tool with mind, flowchart, freehand and etc.
π Repository URL: https://github.com/plait-board/drawnix
π Website: https://drawnix.com
π Readme: https://github.com/plait-board/drawnix#readme
π Statistics:
π Stars: 5.5K stars
π Watchers: 17
π΄ Forks: 432 forks
π» Programming Languages: TypeScript - SCSS - HTML
π·οΈ Related Topics:
==================================
π§ By: https://t.iss.one/DataScienceM
π Description: εΌζΊη½ζΏε·₯ε ·οΌSaaSοΌοΌδΈδ½εη½ζΏοΌε ε«ζη»΄ε―ΌεΎγζ΅η¨εΎγθͺη±η»ηγAll in one open-source whiteboard tool with mind, flowchart, freehand and etc.
π Repository URL: https://github.com/plait-board/drawnix
π Website: https://drawnix.com
π Readme: https://github.com/plait-board/drawnix#readme
π Statistics:
π Stars: 5.5K stars
π Watchers: 17
π΄ Forks: 432 forks
π» Programming Languages: TypeScript - SCSS - HTML
π·οΈ Related Topics:
#productivity #drawing #collaboration #whiteboard #flowchart #mindmap #localfirst
==================================
π§ By: https://t.iss.one/DataScienceM
π₯ Trending Repository: univer
π Description: Build truly AI-native spreadsheets. Univer is a full-stack framework for creating and editing spreadsheets, documents, and slides on both web and server. With Univer MCP, Univer Sheet is driven directly through natural language.
π Repository URL: https://github.com/dream-num/univer
π Website: https://univer.ai
π Readme: https://github.com/dream-num/univer#readme
π Statistics:
π Stars: 10.3K stars
π Watchers: 87
π΄ Forks: 910 forks
π» Programming Languages: TypeScript
π·οΈ Related Topics:
==================================
π§ By: https://t.iss.one/DataScienceM
π Description: Build truly AI-native spreadsheets. Univer is a full-stack framework for creating and editing spreadsheets, documents, and slides on both web and server. With Univer MCP, Univer Sheet is driven directly through natural language.
π Repository URL: https://github.com/dream-num/univer
π Website: https://univer.ai
π Readme: https://github.com/dream-num/univer#readme
π Statistics:
π Stars: 10.3K stars
π Watchers: 87
π΄ Forks: 910 forks
π» Programming Languages: TypeScript
π·οΈ Related Topics:
#productivity #slide #grid #sdk #excel #word #xlsx #spreadsheet #collaboration #office #powerpoint #document #data_table #doc #sheet #ppt #appscript #live_share #univer_mcp
==================================
π§ By: https://t.iss.one/DataScienceM
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π₯ Trending Repository: Pake
π Description: π€±π» Turn any webpage into a desktop app with Rust. π€±π» ε©η¨ Rust θ½»ζΎζε»Ίθ½»ιηΊ§ε€η«―ζ‘ι’εΊη¨
π Repository URL: https://github.com/tw93/Pake
π Readme: https://github.com/tw93/Pake#readme
π Statistics:
π Stars: 41.3K stars
π Watchers: 218
π΄ Forks: 7.7K forks
π» Programming Languages: JavaScript - Rust - Dockerfile
π·οΈ Related Topics:
==================================
π§ By: https://t.iss.one/DataScienceM
π Description: π€±π» Turn any webpage into a desktop app with Rust. π€±π» ε©η¨ Rust θ½»ζΎζε»Ίθ½»ιηΊ§ε€η«―ζ‘ι’εΊη¨
π Repository URL: https://github.com/tw93/Pake
π Readme: https://github.com/tw93/Pake#readme
π Statistics:
π Stars: 41.3K stars
π Watchers: 218
π΄ Forks: 7.7K forks
π» Programming Languages: JavaScript - Rust - Dockerfile
π·οΈ Related Topics:
#music #rust #productivity #mac #youtube #twitter #programming #high_performance #gemini #openai #windows_desktop #linux_desktop #tauri #mac_desktop #excalidraw #llm #no_electron #chatgpt #gemini_ai #deepseek
==================================
π§ By: https://t.iss.one/DataScienceM
In Python, building AI-powered Telegram bots unlocks massive potential for image generation, processing, and automationβmaster this to create viral tools and ace full-stack interviews! π€
Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots
https://t.iss.one/DataScienceMπ¦Ύ
# 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(
"β¨ 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("β 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"π¨ Generated: *{prompt}*",
parse_mode="Markdown"
)
except Exception as e:
await update.message.reply_text(f"π₯ 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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β€1
π How to Create Professional Articles with LaTeX in Cursor
π Category: LLM APPLICATIONS
π Date: 2025-11-25 | β±οΈ Read time: 9 min read
Streamline your academic and technical writing by creating professional articles and presentations with LaTeX directly in Cursor. This guide demonstrates how to leverage the editor to rapidly produce high-quality, typeset documents, enhancing your productivity and workflow for polished, professional results.
#LaTeX #Cursor #TechnicalWriting #Productivity
π Category: LLM APPLICATIONS
π Date: 2025-11-25 | β±οΈ Read time: 9 min read
Streamline your academic and technical writing by creating professional articles and presentations with LaTeX directly in Cursor. This guide demonstrates how to leverage the editor to rapidly produce high-quality, typeset documents, enhancing your productivity and workflow for polished, professional results.
#LaTeX #Cursor #TechnicalWriting #Productivity
β€2
π How to Scale Your LLM usage
π Category: AGENTIC AI
π Date: 2025-11-29 | β±οΈ Read time: 7 min read
Effectively scaling your Large Language Model (LLM) usage is crucial for unlocking major productivity improvements. This guide outlines key strategies for expanding LLM integration from proof-of-concept to full-scale deployment, enabling your teams to harness the full power of AI for enhanced operational efficiency and innovation. Learn the best practices for managing costs, ensuring reliability, and maximizing the impact of LLMs across your organization.
#LLM #AIScaling #Productivity #ArtificialIntelligence
π Category: AGENTIC AI
π Date: 2025-11-29 | β±οΈ Read time: 7 min read
Effectively scaling your Large Language Model (LLM) usage is crucial for unlocking major productivity improvements. This guide outlines key strategies for expanding LLM integration from proof-of-concept to full-scale deployment, enabling your teams to harness the full power of AI for enhanced operational efficiency and innovation. Learn the best practices for managing costs, ensuring reliability, and maximizing the impact of LLMs across your organization.
#LLM #AIScaling #Productivity #ArtificialIntelligence
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