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.
