Tag · 13 posts
#llm
Always-on assistants that are asleep most of the day
I wanted an assistant that is always there. I write to it at 7am and the answer is ready at 7:01. It remembers what I told it last week. I don't have to start it, and I don't have to explain myself again.
aiBuilding Event-Driven Agents with Azure Functions
Microsoft now has several ways to build AI agents. You can create prompt agents in Foundry, build agentic workflows with Logic Apps, or deploy your own agent code as a Foundry hosted agent. There is another option that fits a different type of problem: the Azure Functions serverless agents runtime. This runtime lets you define…
aiHosting an AG-UI Agent on Microsoft Foundry
A while back I wrote about building an AI agent server with AG-UI and the Microsoft Agent Framework. That post walked through what AG-UI is, how you stand up a small agent server, and how a web client talks to it. Quick recap before we move on: AG-UI is a protocol between a frontend and…
aiBuilding an AI Agent Server with AG-UI and Microsoft Agent Framework
In this post, I want to talk about the Python backend I built for an AG-UI demo project. It is part of a larger project that also includes a frontend that uses CopilotKit: This post discusses the Python AG-UI server that is built with Microsoft Agent Framework. All code is on GitHub: https://github.com/gbaeke/agui. Most of…
aiCreating presentations with Microsoft Agent Framework and GAMMA API
Introduction Imagine automating the creation of professional presentations through a coordinated series of intelligent agents. In this blog post, we’ll explore how to build a workflow that combines research, outline generation, content creation, and design, all orchestrated through the Microsoft Agent Framework. We’ll build a practical example that generates presentations using: Azure OpenAI Responses API for…
aiEnd-to-end authorization with Entra ID and MCP
Building an MCP server is really easy. Almost every language and framework has MCP support these days, both from a client and server perspective. For example: FastMCP (Python, Typescript), csharp-sdk and many more! However, in an enterprise scenario where users use a web-based conversational agent that uses tools on an MCP server, those tools might…
aiDeploying a multi-agent solution with MCP and A2A to Azure Container Apps
In previous posts, we discussed multi-agent scenarios, how A2A servers work (here and here) and how to deploy the infrastructure to host a multi-agent application on Azure with Azure Container Apps and AI Foundry. In this post, we will take a look at deploying the different components of the solution as containers in Azure Container…
aiUsing tasks with streaming in Google Agent2Agent (A2A)
In a previous post we created a simple A2A agent that uses synchronous message exchange. An A2A client sends a message and the A2A server, via the Agent Executor, responds with a message. But what if you have a longer running task to perform and you want to inform the client that the task in…
aiGoogle’s A2A: taking a closer look
In the previous post, I talked about options to build multi-agent solutions. The last option used Google’s A2A. A2A provides a wrapper around your agent, basically a JSON-RPC API, that standardizes how you talk to your agent. In this post we take a closer look at the basics of A2A with simple synchronous message exchange.…
aiLoad balancing OpenAI API calls with LiteLLM
If you have ever created an application that makes calls to Azure OpenAI models, you know there are limits to the amount of calls you can make per minute. Take a look at the settings of a GPT model below: Above, the tokens per minute (TPM) rate limit is set to 60 000 tokens. This…
aiWriting your first flow with Prompt Flow in Visual Studio Code
In this blog post, we will create a flow with Prompt Flow in Visual Studio Code. Prompt Flow is a suite of development tools to build LLM-based AI applications. It tries to cover the end-to-end development cycle, including prototyping, testing and deployment to production. In Prompt Flow, you create flows. Flows link LLMs (large language…
aiUsing Azure Database for PostgreSQL as a vector store
When we build LLM applications, there is always a recurring question: “What vector store will we use?”. In Azure, there are several native solutions. Some of them were discussed in previous posts. Azure Cognitive Search: supports vector search but also hybrid search with semantic reranking as discussed here Azure Redis Cache Enterprise: check my blog…
aiSemantic Kernel Planner 101
Introduction If you are a developer who wants to build AI-first apps with natural language processing and large language models, you might be interested in Semantic Kernel (SK), a lightweight and open-source SDK that aims to simplify the integration of AI with conventional programming languages. SK is part of the CoPilot Stack and Microsoft is…
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