https://tube.grossholtz.net/videos/watch/1a22ed52-830d-4318-8994-a6905fd5e8a2 Learn how to leverage the free Llama 3.2 Vision multimodal models in FlowiseAI to build powerful image processing applications without writing code. This comprehensive tutorial demonstrates three practical use cases including extracting structured data from invoices, building conversational image assistants, and creating a multi-agent workflow for optimizing YouTube thumbnails and titles. Discover how to set up Ollama, configure the vision model, and create sophisticated flows that combine image analysis with natural language processing capabilities. 🙏 Support My Channel: Buy me a coffee ☕ : https://www.buymeacoffee.com/leonvanzyl PayPal Donation: https://www.paypal.com/ncp/payment/EKRQ8QSGV6CWW 📑 Useful Links: Getting Started with FlowiseAI: https://youtu.be/nqAK_L66sIQ FlowiseAI Cloud: https://flowiseai.com/auth/signup?referralCode=LEONVZ Sequential Flows Crash Course: https://youtu.be/6LbvgTbS0BE Ollama & Llama 3.2 RAG: https://youtu.be/lJOZiRoZNJw 🧠 I can build your chatbots for you! https://www.cognaitiv.ai 🕒 TIMESTAMPS: 00:00 - Introduction 01:03 - Ollama setup 01:57 - LLM Chain with Structured Output 06:30 - Conversational Assistant 08:01 - Multi Agent with Images Mon, 06 Apr 2026 05:07:43 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://tube.grossholtz.net https://tube.grossholtz.net/client/assets/images/icons/icon-512x512.png https://tube.grossholtz.net/videos/watch/1a22ed52-830d-4318-8994-a6905fd5e8a2 All rights reserved, unless otherwise specified in the terms specified at https://tube.grossholtz.net/about and potential licenses granted by each content's rightholder.