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Imagine you have a Microsoft Agent Workflow that continuously processes a high-volume stream of incoming data. The data flows through multiple executors responsible for validation, summarization and d
Disclaimer : This article is highly technical and assumes that you have strong understanding on the concepts of Edges and Executors in MAF. If you are not comfortable with Executors and Edges and how
My previous article focused on introduction of workflows in MAF along with a basic overview of Executors, Edges and Events. This article will explore different workflow orchestration patterns availabl
Before we dive into the details of the topic of this article, lets first understand why we need workflows in Agentic AI systems. Most people might argue that when agents can make decisions, make tool
In MAF, if no external storage provider is configured, the chat history by default is stored in server memory. The InMemoryChatHistoryProvider component stores chat messages in a StateBag where the St
We all know that LLM backed agents scale at on demand execution. They perform well when prompted, execute tasks and return results almost instantly. But not all business all problems are request-drive
My previous article explored how to leverage Dependency Injection (DI) for function calling. However, that approach was limited because of its ability to execute a single function per request with no
My previous article on Microsoft Agent Framework (MAF) was focused on Dependency Injection (DI) in MAF. In that article I demonstrated how AIToolscan be registered in the service container through DI
After working on Semantic Kernel (SK) for sometime and then gradually shifting focus towards Microsoft Agent Framework (MAF), I’ve personally started to like MAF over SK. Implementation through SK had
