Agents in 60 lines of python : Part 1

The Agent Function Lesson 1 of 9 — A Tour of Agents Every time you send a message to ChatGPT, Claude, or any LLM — your app makes one HTTP POST request and gets a response back. That's it. No magic. No framework. One function. This is where agents start. What is an agent, really? Strip away the buzzwords and an AI agent is a pipeline with four steps: Your message → agent() → POST /completions → Response Your message goes in. A function wraps it into the right format. An HTTP call goes out. A response comes back. That flow diagram is the entire architecture of Lesson 1. There's no orchestration engine. No agent framework. Just a function that talks to an API. The function Here's the core of it — a function called ask_llm : async def ask_llm ( messages ): resp = await pyfetch ( " https://api.groq.com/v1/chat/completions " , method = " POST " , headers = { " Authorization " : f " Bearer { KEY } " }, body = json . dumps ({ " model " : " llama-3.3-70b " , " messages " : messages }) ) data =