Studio from Microsoft to rapidly prototype Multi Agent AI Applications

What you will learn

Understanding of the building blocks of Autogen Studio – Skills, Models, Agents, Workflow

Installation and Launch of Autogen Studio using Anaconda and Docker

Declaratively define and modify agents and multi-agent workflows through a point and click interface

Use UI to create chat sessions with the specified agents and view results (e.g., view chat history, generated files, and time taken)

Explicitly add skills to agents and accomplish more tasks.

Linking Agents to Open Source Models via Ollama application

Why take this course?

Autogen Studio – Build Low Code Multi Agent AI Applications

AutoGen Studio is an open-source, low-code interface developed by teams at MicrosoftΒ  to help in rapidly prototype AI agents, enhance them with skills, compose them into workflows and interact with them to accomplish tasks.

This course is a hand-on session to provide a deeper understanding on how multiple agents are linked into workflows to let a team of AI agents work for you to accomplish your tasks .

Course Overview :

1.Introduction to Autogen Studio

2.Getting Started With Autogen Studio

– Setting up environment (Conda + OpenAI)

– Navigating Studio Dashboard

3.Understanding Building Blocks of Autogen Studio


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– Learn to create Skills and Configure Models

-Learn to create Agents , integrate them into Workflows and create sessions in Playground to execute Workflows

4.Advanced Techniques

– Walkthrough of Multi AI Agent workflow execution– Creating Skill

– Walkthrough of Multi AI Agent workflow execution – Generating PDF

– Walkthrough of Multi AI Agent workflow execution – Group chat with Multiple Agents to create Travel Itinerary

5.Using Open Source LLMs with Autogen Studio

-Step by Step instructions to link Agents to Llama3.1 model (Meta) running on local system, using Ollama tool

6.Launching Autogen Studio in Docker Container (Safe Code Execution)

-Step by Step instructions to install docker and launch Autogen Studio application in Docker Container

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