How to Get Started with Python and AI Agents Using LangGraph

Artemis: Code That Evolves, Not Just Generates In our recent paper (https://lnkd.in/eYMCm2JH), we showed how Meta-Prompted Code Optimization can deliver up to 19% faster code across real C++ and Python projects. What’s a meta-prompt? Instead of asking an LLM directly — “Optimize this Python function for speed” - we first ask it to design the best possible prompt for the task, given the project, model, and constraints. That prompt itself then evolves over iterations, guiding the LLM to generate progressively better code. This is the philosophy behind Artemis: ✅ Automates context gathering (project, task, model). ✅ Evolves both prompts and code through intelligent search. ✅ Validates improvements with real benchmarks. The future isn’t just AI-generated code. It’s AI-evolved code — prompts and code — validated for production. #AI #LLM #CodeOptimization #GenAI #Sustainability #TurinTechAI

🚀 From code generation to code that runs: Meta Prompting takes LLM optimization a step further. Our ASE 2025 paper, highlighted here by Mike Basios, reflects TurinTech AI’s ongoing research leadership in making AI-generated code enterprise-ready. By combining prompting strategies with evolutionary optimization, we’re advancing how LLMs can produce cleaner, validated, and more efficient code at scale. #AI #LLM #MetaPrompting #CodeOptimization #AgenticAI #ArtemisInside

Ready to move beyond basic chatbots? 🤖 This blueprint covers how to build modern, autonomous AI agents in Python. We dive into the essentials that make agents efficient, safe, and truly useful. Key takeaways: 🔹 asyncio: The non-negotiable foundation for responsiveness. 🔹 Agents, Guardrails, & Handoffs: The three pillars of a robust system. 🔹 Practical Code: From the official OpenAI API to simplified frameworks. If you're building in the AI space, this is a must-read to understand how to turn a powerful LLM into an agent that can actually get things done. Check out the full guide on Medium: https://lnkd.in/d7_CUspA #AI #Python #ArtificialIntelligence #Agents #OpenAI #Developer #LLM

💡 Python is the new Excel Macro and will dominate companies! Just as Excel transformed the way businesses operated decades ago, Python is doing the same, only with much greater power. It has become the language of AI and is everywhere: from process automation to scripting by co-pilots and end users. According to the TIOBE Index, Python usage grew +26% this year and continues to accelerate. The big challenge for IT is: how to manage and scale these automations securely and with governance? ▶ In this video by Lorhan Caproni, you'll learn how BotCity helps your company transform this inevitable growth into strategic value and real control. If you want to delve deeper into this topic, visit: https://hubs.la/Q03Gh7kz0 #BotCity #Python #AI #Automation #OperationalEfficiency #Governance #Innovation #DigitalTransformation

🚀 Just built a Generative AI PDF Q&A Chatbot! 📂 Upload any PDF → 💬 Ask questions → 🤖 Get instant AI-generated answers with source references. Key Features: Interactive web app built with Streamlit Uses Groq LLM for generative answers HuggingFace embeddings for semantic search Shows source pages for transparency Tech Stack: Python | Streamlit | LlamaIndex | Groq | HuggingFace This project demonstrates practical GenAI in action, enabling knowledge extraction from documents for research, corporate, or educational purposes. #GenAI #AI #MachineLearning #Streamlit #Python #DataScience #LlamaIndex #Groq #HuggingFace #ProjectShowcase

🚀 UV – the new speed-demon in Python packaging UV (by Astral, Rust-based) is making waves as a faster, cleaner alternative to the traditional pip-based workflow. It delivers much faster installs, streamlined project scaffolding, and stricter, more transparent dependency handling. 💡 Some highlights: • 10-100× faster installs in many cases • Automatic virtual environment usage by default • Better error/diagnostics when specs are violated • Strong compatibility with existing pip + pip-tools workflows (just about all basics work out of the box) ⚠️ Downsides: some pip features are still missing; and stricter behavior may require updating certain dependency specs. But overall, UV is proving to be a worthwhile upgrade for many projects. Reference : https://docs.astral.sh/uv/ 🎯 If you’re tired of slow installs or messy environment setups, it might be time to give UV a try. 💬 Have you tried UV yet? What benefits or drawbacks have you experienced compared to pip? #Python #DeveloperTools #OpenSource #AI #MachineLearning #Tech #Innovation #SoftwareEngineering

Built entirely in Python, this agent can search, analyze, and synthesize information from large-scale local data without relying on external web APIs. It uses local embeddings for document indexing, supports multi-step reasoning to break down complex queries, and efficiently retrieves relevant information. Optional enhancements include generating coherent research summaries, interactive follow-up queries, AI explanations of reasoning steps, and exporting results in structured formats like PDF or Markdown. Check out the working demo in the video! #SRMHacksWithCodemate CodeMate® AI SRM Institute of Science and Technology (SRMIST)

Day 7/365 – Build AI Agents with Python ✅🤖 ✅ Start with the basics – Learn Python fundamentals + libraries like requests, json, and asyncio. 🔑 Add AI power – Use frameworks like LangChain, LlamaIndex, or OpenAI API to connect models with real-world data. 👉 Make it useful – Automate tasks: chatbots, research assistants, content generators, or workflow bots. ⚡ Pro tip: Combine APIs + memory + logic → you get an AI agent that thinks and acts, not just chats. ✨ Rule of thumb: AI agents aren’t built in one go — they evolve as you stack tools, logic, and creativity. ❓What’s the first AI agent you’d love to build? #Python #AIAgents #ArtificialIntelligence #MachineLearning #OpenAI #LangChain #Automation #100DaysOfCode #CodingTips #DeveloperJourney #BuildInPublic #FutureOfWork

Ever wondered how to build your own digital assistant? 🤖 The world is moving towards agentic AI, where programs don't just follow commands but can reason and act on their own to achieve a goal. This is a game-changing skill for any developer. I've put together a step-by-step guide designed to help you build your very first AI agent using Python. We'll move from setup to execution, focusing on clarity and practical application. You'll learn: How to use an agentic framework. How to give your AI tools to interact with the world (like web search). The basics of prompt engineering. Ready to build something truly intelligent and add a powerful skill to your toolkit? 🔗 Check out the full article here: https://lnkd.in/gUWqkHuR #AI #AgenticAI #Python #MachineLearning #SoftwareDevelopment #TechSkills #Coding #BuildInPublic

Unlocking creativity and efficiency with the power of Python and Generative AI! 🚀 Today, automation and AI aren't just buzzwords—they're practical drivers of real value for individuals and businesses. Whether it's automating content creation, processing data, or building innovative tools, Python empowers us to turn complex workflows into simple, repeatable processes. In this experiment, I combined generative AI models with Python scripting to automate digital content creation—streamlining tasks, boosting productivity, and opening new opportunities for creative exploration. What’s your favourite way to use Python and AI for automation? Let’s discuss ideas, tools, and recent trends in the comments! 👇 #Python #GenerativeAI #Automation #AIProductivity #TechTrends #Innovation