IMPORTANT: You have to install Ollama on your machine. Learn how to create a powerful, AI‑driven web‑search agent in Python using Ollama free local LLM models! In this step‑by‑step tutorial we’ll walk through the entire development process—from setting up your environment with dotenv and the Ollama API, to writing the code that performs live web searches, summarizes the results with a large language model, and saves a Markdown summary. What you’ll get: • A clean, ready‑to‑run Python script (full source code provided) • Explanation of each function (summarize_search_results, ollama_websearch, and main) • Tips for handling API keys securely with .env files • Debugging tricks for common pitfalls (e.g., undefined variables, response handling) • A live demo where we search for “Main news in Europe today” and see the generated summary instantly Why Ollama? Ollama lets you run large language models locally or in the cloud, giving you full control over privacy, cost, and performance. This tutorial uses the gpt-oss:120b-cloud model, but you can swap it for any other model you prefer. Prerequisites: • Basic Python knowledge • An Ollama account & API key (free tier available) • Python 3.9+ installed on your machine Resources & Links: • Ollama API docs – Don’t forget to 🔔 Subscribe for more AI‑coding tutorials 👍 Like the video if you found it helpful 💬 Drop your questions or suggestions in the comments!