Let me walk you through something I have been experimenting with lately, running a local AI agent that detects hate speech, powered by Google's Gemma 4 model and the CrewAI framework, all without calling any paid API. No keys, no credits. Just a local model and python. Let me explain how I put this together. Why Gemma + CrewAI? Most CrewAI tutorials you will find online default to GPT-4 or Claude. That is fine, but what if you want to run everything locally, maybe for privacy or cost reasons, or just to understand the stack at a deeper level? Well, I could have gone with Meta's Llamma3.2 3B model, that is a good opensource alternative as well, but Gemma 4 is new and I just wanted to try it, but you can use any opensource model available on Hugging face. The model I used is google/gemma-4-E2B-it , a 2-billion parameter instruct-tuned version of Google's Gemma 4. It is light enough to run on Colab GPU without any resource crunches, and it loads via Hugging Face transformers library.…