2 articles tagged with "Python"

An agentic workflow in Python is a set of model calls, tools and plain functions wired into a fixed shape: a chain, a fan-out, a router or a loop. The model makes decisions inside each step, but your code decides which steps exist. You do not need LangGraph for that. You need a graph runner, a clean handoff between steps, and a way to call different providers.

This guide builds each common AI agent orchestration pattern with Intelli, an Apache 2.0 Python library for multi-model agent flows. The examples mix OpenAI, Claude and Gemini in one flow and can run on a local Ollama model. It closes by comparing Intelli with LangGraph, CrewAI and plain code, including where each of them wins.

Here is how to build an AI agent in Python without a big framework: give a model a short list of functions, run a loop that executes the calls it asks for, send the results back, and stop after a fixed number of steps. That loop is the agent. Everything else is guardrails.

In this guide you will build an order status agent in under 100 lines of plain Python on top of the Intelli Chatbot. The same code runs on OpenAI, Claude or a local Ollama model by changing one constructor and the model name, and you will see exactly where a tiny local model falls short.