I just created my very first local AI agent using: - **[Python](https://www.python.org/)** - **[LLaMA 3](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)** running locally via **[Ollama](https://ollama.com/)** - All offline, private, and token‑free Here’s what `agent-hello` does: ```python ## main.py import requests def talk_to_llama(prompt): res = requests.post("http://localhost:11434/api/generate", json={ "model": "llama3", "prompt": prompt, "stream": False }) return res.json()["response"] print("Agent says:\n", talk_to_llama("Hello, who are you?")) ``` That’s it. A little hello agent on my M1 Mac. It’s now a sovereign little AI machine. ## How I Got It Running ### 1. Installed Ollama [Ollama Download](https://ollama.com/) ### 2. Pulled a model ```bash ollama pull llama3 ``` ### 3. Set up a Python virtualenv ```bash mkcd agent-hello python3 -m venv .venv source .venv/bin/activate pip install requests ``` ### 4. Ran `python3 main.py` — and boom, the agent replied. ```bash python3 main.py ``` ![AI Agent with Llama3](/content/uploads/2025/05/agent-hello.webp) ## Why This Matters - **Privacy — Zero data leakage** All inference runs on‑device. Your prompts, code snippets, and business secrets never touch an external server. This eliminates the compliance nightmare of accidental data exfiltration. - **Cost — Token‑free, cheap, predictable** No per‑token fees, no hidden bandwidth charges. Once the model is on your SSD (or external drive), you pay only electricity and the one‑time storage cost—orders of magnitude cheaper than any managed API. - **Sovereignty — Control without downtime** You own the stack. No reliance on third‑party SLA, rate limits, or unexpected price hikes. Your agent stays up even if the cloud goes down, and you can patch, upgrade, or fork it at will. In short, a local AI agent turns the “pay‑per‑call” model on its head: you get powerful LLM capabilities, full control, and a predictable budget—all from a single M1 Mac. **END_OF_REPORT** 🌿✨