L-16 | Understanding Agno (formerly Phidata) : Multimodal Agentic AI Framework

Learn everything about the *Agno framework* and how to build *multi-modal AI agents* in this detailed tutorial! Discover why Agno is different from LangChain, LangGraph, and CrewAI, and see how it enables *ultra-lightweight agents* in microseconds. 📥 Download the complete source code: 🔗 GitHub: https://github.com/codewithaarohi/Age... 📌 *What You’ll Learn:* 1️⃣ What Agno is and why it stands out from LangChain, LangGraph, and CrewAI 2️⃣ How Agno creates agents in *microseconds* 3️⃣ Why Agno is *incredibly lightweight* (6.5 KiB per agent!) 4️⃣ How to build *multi-modal AI agents* using Agno (text, images, audio, video) 5️⃣ Comparison with LangGraph: building *image and audio-based agents* 6️⃣ Real-world use cases like a *Healthcare Assistant* and *Audio Transcription Agent* 💬 Questions or need assistance? Contact me at *[email protected]* 🔔 Don’t forget to *like, comment, and subscribe* for more tutorials on **Agentic AI frameworks and generative AI**! #AgenticAI #GenerativeAI #AgnoFramework #MultiModalAI #LightweightAI #AIAgents #LangChainVsAgno #LangGraphVsAgno #AIWorkflow #PythonAI