Step by Step guide to develop AI Multi-Agent system using Microsoft Semantic Kernel and GPT-4o

Sophia Lagerkrans-Pandey

Today we want to highlight a recent Medium article published here: Step by Step guide to develop AI Multi-Agent system using Microsoft Semantic Kernel and GPT-4o | by Akshay Kokane | Jun, 2024 | Medium

We’ve included a few excerpts below, but click here to read the full article. A Microsoft colleague, Akshay Kokane, details how to develop an AI Multi-Agent system using Microsoft Semantic Kernel and GPT-4o. This blog series will equip you to not only understand AI agents but also build your own using the powerful Semantic Kernel framework. Semantic Kernel boasts a smooth onboarding process, effortlessly manages multiple Large Language Models (LLMs), and provides pre-built features like planners to simplify orchestration.

From Chatbots to AI Assistants: The Evolution of AI Agents

Since the launch of GPT models, terms like “chatbot,” “RAG,” “Copilot,” and now “agent” have dominated the AI landscape. As Semantic Kernel’s documentation clarifies: “An agent is an artificial intelligence that can answer questions and automate processes for users.” With Semantic Kernel, you can build a wide range of agents, from simple chatbots to fully automated AI assistants.

Building Multi-Agent Software Development Team with Semantic Kernel and GPT-4o

We’ll explore the exciting world of building AI agents using Semantic Kernel and the OpenAI Assistant API. We’ll simulate a collaborative development process, outlining the roles of key team members:

  • Product Manager: The maestro of the project, crafting a development plan that translates user needs into actionable steps.
  • Software Engineer: The coding wizard, responsible for implementing the plan and bringing the agent to life.
  • Project Manager: The guardian of quality, ensuring the final product meets all specifications and receives the green light for release.

 

Summary

We’re always interested in hearing from you. If you have feedback, questions or want to discuss further, feel free to reach out to us and the community on the discussion boards on GitHub! We would also love your support, if you’ve enjoyed using Semantic Kernel, give us a star on GitHub.

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  • Christian Rodriguez 0

    multi agent is nice and all, but can we get “Normal” assitant v2 support in semantic kernel without multiagent abstraction? One nice feature of assistant api (including v2) is that it saves threads automatically so you can save conversation without additional effort, but that’s been “abstracted away” in semantic kernel and you can’t recover a thread: it’s created automatically under the hood and you can’t recover it

    assistant v2 with file search is very powerful and it would be nice to have sematic kernel power to use plugins. That should be your priority in my opinion. Not multiagent BEFORE fully supporting assistant api v2

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