AI Agent Playground (Python + Anthropic)
An exploratory playground for building and testing agent patterns in Python, including tool calling, short-term memory, and local-first secret handling.
Project Overview
This project is a personal playground to learn AI agent development in pure Python, with a focus on Anthropic models and APIs.
The goal was to understand the basics by building a minimal agent loop, wiring tool calls, and handling conversation state directly in code.
Why I Built It
- Get comfortable building agents in pure Python.
- Explore Anthropic model behavior and tool-calling flow.
- Keep the setup simple so it is easy to modify and experiment with.
What It Includes
- A lightweight agent loop using Anthropic Messages API.
- Tool-calling with a calculator example.
- Short-term conversation memory across turns.
- Local API key handling via
.env.local. - A small tool registry in
tools/__init__.py.
Playground Direction
This repo is intentionally small so it can be taken further: you can play around from here, add more tools, and test new interaction patterns quickly.
For example, you can add: - greeting tools - formatting/utility tools - domain-specific tools for your own use cases
Notes
Adapted from Leonie Monigatti's article and then customized for learning and experimentation: https://leoniemonigatti.com/blog/ai-agent-from-scratch-in-python.html