Peteos Documentation

Peteos is a library for developing agentic software, built on Simple Object-Agentic Programming (sOAP) — a paradigm that marries object-oriented programming with AI agents. Agentic objects are objects that can think, decide, and interact with their environment on their own.

Object-agentic programming lets you write normal Python classes and expose their parts to an AI agent. Mark methods with @tool, call invoke_agent(), and the agent reasons about which tools to use to fulfill your task.

Getting Started

Page	Description
Getting Started	Installation, LLM backend setup, and your first agentic objects
Introduction	A brief introduction to the sOAP paradigm
sOAP	The sOAP philosophy, core principles, and mental model for agentic objects

Learn

Page	Description
Concepts	Deep dives: composition, invocation, state and persistence, media handling
Best Practices	Proven patterns: guardrails, unit testing — how to build reliable agentic systems
Examples	Runnable code: hello pete, grocery list, stock portfolio analyzer, and more

Reference

Page	Description
API Index	All classes, decorators, and configuration documented by name

Advanced

Page	Description
Advanced Index	Internal classes and concepts for debugging, extending, and building on top of Peteos