In this video, I build a practical Gemma 3 AI agent that runs fully local using Ollama, and I wire it into an agentic workflow so it can parse PDFs and URLs and answer questions on top of that content. The whole point is speed + control: instead of shipping your documents to a cloud model, I show how to keep everything on your machine while still getting an “agent-like” experience for document analysis and summarization. I connect Gemma 3 with an AGNO-based agent setup and walk through the end-to-end flow: install/run Gemma 3 via Ollama, plug the model into the agent, ingest a PDF or a web URL, and then query it like a research assistant. I also do a quick performance-style demo comparing how this feels versus previous local LLM setups and cloud options like Gemini—especially for fast iterations when you’re prototyping RAG-ish document workflows. If you’re new to agents, I also point you to my earlier videos on agent fundamentals and agentic design patterns so you don’t treat this like “just another chatbot,” but as a reusable system design pattern.