The Launch of "AI Agents for Beginners": Your Gateway to Building Intelligent Systems
🌱 Getting Started Each lesson covers fundamental aspects of building AI Agents. Whether you're a novice or have some experience, you'll find valuable insights and practical knowledge. We also support multiple languages, so you can learn in your preferred language. To see the available languages, click here. If this is your first time working with Generative AI models, we highly recommend our "Generative AI For Beginners" course, which includes 21 lessons on building with GenAI. Remember to star (🌟) this repository and fork it to run the code! 📋 What You Need The course includes code examples that you can find in the code_samples folder. Feel free to fork this repository to create your own copy. The exercises utilize Azure AI Foundry and GitHub Model Catalogs for interacting with Language Models: Github Models - Free / Limited Azure AI Foundry - Azure Account Required We also leverage the following AI Agent frameworks and services from Microsoft: Azure AI Agent Service Semantic Kernel AutoGen For more information on running the code for this course, visit the Course Setup. 🙏 Want to Help? We welcome contributions from the community! If you have suggestions or spot any errors, please raise an issue or create a pull request. If you encounter any difficulties or have questions about building AI Agents, join our Azure AI Community on Discord. 📂 Each Lesson Includes A written lesson located in the README (Videos Coming March 2025) Python code samples supporting Azure AI Foundry and Github Models (Free) Links to extra resources to continue your learning 🗃️ Lessons Overview Intro to AI Agents and Use Cases Exploring Agentic Frameworks Understanding Agentic Design Patterns Tool Use Design Pattern Agentic RAG Building Trustworthy AI Agents Planning Design Pattern Multi-Agent Design Pattern Metacognition Design Pattern AI Agents in Production 🌐 Multi-Language Support We offer translations in several languages and will updating these on a regular basis. 🚀 Go Fork or Clone this repo and get started on your AI Agents journey 🤖 at https://aka.ms/ai-agents-beginnersBuilding AI Agent Applications Series - Using AutoGen to build your AI Agents
In the previous content, we learned about AI Agent. If you didn't read it, please read my previous content - Understanding AI Agents. We have many different frameworks to implement AI Agents. AutoGen from Microsoft is a relatively mature AI Agents framework. Now AutoGen is mainly based on two programming languages .NET and Python. The more mature version is the Python version. The content in this article is mainly based on the Python version https://microsoft.github.io/autogen. If you want to learn the .NET version, you can visit here https://microsoft.github.io/autogen-for-netMicrosoft Semantic Kernel and AutoGen: Open Source Frameworks for AI Solutions
Explore Microsoft’s open-source frameworks, Semantic Kernel and AutoGen. Semantic Kernel enables developers to create AI solutions across various domains using a single Large Language Model (LLM). AutoGen, on the other hand, uses AI Agents to perform smart tasks through agent dialogues. Discover how these technologies serve different scenarios and can be used to build powerful AI applications.
DocAider: Automated Documentation Maintenance for Open-source GitHub Repositories
Code–level documentation of a software system provides explanations of the code functionality and usages. Documentation is crucial for giving clear insights into the code for end–users and future developers. However, creating and updating documentation manually is a demanding task, requiring significant resources and labour. With the advancement of generative AI, there is a potential to reduce human labour in documentation tasks significantly. We propose DocAider, an automation tool powered by GPT–4 that integrates the processes of documentation generation and update. DocAider can generate comprehensive and structured documentation in markdown format and update it in response to any changes made in pull requests. The mission of DocAider is to reduce developers’ burden on maintaining documentation for GitHub repositories.Building AI Agent Applications Series - Assembling your AI agent with the Semantic Kernel
In the previous series of articles, we learned about the basic concepts of AI agents and how to use AutoGen or Semantic Kernel combined with the Azure OpenAI Service Assistant API to build AI agent applications. For different scenarios and workflows, powerful tools need to be assembled to support the operation of the AI agent. If you only use your own tool chain in the AI agent framework to solve enterprise workflow, it will be very limited. AutoGen supports defining tool chains through Function Calling, and developers can define different methods to assemble extended business work chains. As mentioned before, Semantic Kernel has good business-based plug-in creation, management and engineering capabilities. Through AutoGen + Semantic Kernel, powerful AI agent solutions can be built.Autogen: Microsoft’s Open-Source Tool for Streamlining Development
Are you a technical student looking for a tool that can help you generate high-quality code, documentation, and tests for your projects? If so, you might want to check out AutoGen a framework that enables development of large language model (LLM) applications using multiple agents that can converse with each other to solve tasks.
