Multi-Agent Workshop

This project showcases autogen (0.4) by presenting a set of simple scripts that create different type of agents and interactions between them with the purpose of highlighting the main capabilities of the agentic framework. This repo is based on https://github.com/krishsub/MultiagentHackathon.

Getting Started

Prerequisites

• Opean AI service deployed with GPT-4o

• Azure Container Apps Session Pool

• dev container option: The project provides a devcontainer configuration that can be used with github codespaces or your own local dev container. So, if you opt for this, you need to have docker in your system

• venv option: if you have python > 3.8 you could choose to create a venv and install all the requirements there.

Leverage AZD to deploy the prerequisites

You can leverage the Azure Developer CLI, azd for short, to deploy the prerequisites to a subscription. It'll create the resources and export some env vars which you can use to run the exercises. To leverage azd you need to have it installed and configured. After that, all it takes is a simple azd up and the components will be installed.

For a detailed explanation on what it deploys, check out the README.md in the infra directory.

After the components have been deployed, you can navigate to AI Foundry and obtain the Open AI Key and Endpoint. The Open AI endpoint, as well as the Azure Container Apps endpoint will be stored in the azd environment variables. You can leverage those as well. The Open AI Key is not exposed in this manner for security considerations.

Quickstart

Environment Variables

For this set of scripts, a gpt-4o model instance was used. Create a .env file with your Azure OpenAI credentials in the src folder:

AZURE_OPENAI_API_KEY=your_api_key
AZURE_OPENAI_ENDPOINT=your_endpoint

Installation

Choose one of the following methods to run the different scripts. Make sure to cd src.

Option 1: Using uv (Recommended)

uv is a fast Python package installer and runner. If you haven't installed it yet:

curl -LsSf https://astral.sh/uv/install.sh | sh

Then run the script directly (this will automatically install dependencies):

uv run 0X_SCRIPT_NAME.py

Option 2: Using pip

1. Install dependencies:

   pip install -r requirements.txt

2. Run the script:

   python 0X_SCRIPT_NAME.py