Category Archives: AI
An Overview of Agent Memory for .NET
The ability for Microsoft Agent Framework agents to retain and utilize knowledge across interactions is critical. One solution for this is Agent Memory for .NET, a cutting-edge, mind-blowing, graph-native memory engine that leverages the robust capabilities of Neo4j as its … Continue reading
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Microsoft Agent Framework and Foundry
In the .NET development world the two most significant frameworks for AI are Microsoft Agent Framework and Microsoft Foundry. Together, they create a powerful ecosystem for building, deploying, and managing AI agents that can automate tasks, respond to user queries, … Continue reading
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Managing Secrets in Microsoft Agent Framework
In the realm of software development, managing configuration values and sensitive information is a critical aspect that can significantly impact the security and functionality of applications. Developers often find themselves at a crossroads when deciding how to store configuration values, … Continue reading
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Detecting AI
I fed the first half of one of the blog posts generated by my demonstration program to Pangram. Here are the results: Bzzzz Still your turn.
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ChatClient Middleware vs. Agent Middleware
As noted in a previous post, middleware plays a pivotal role in enhancing the functionality and observability of agents. The Microsoft Agent Framework utilizes two primary types of middleware: ChatClient Middleware and Agent Middleware. Understanding the distinctions between these two … Continue reading
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Long-term memory in Microsoft Agent Framework
Long-term memory in AI agents refers to the ability to retain information across multiple interactions and sessions. This is essential for creating a more personalized user experience, as it allows agents to recall user preferences, past conversations, and contextual information. … Continue reading
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LangChain vs Microsoft Agent Framework
In the rapidly evolving landscape of artificial intelligence, developers are presented with a myriad of frameworks to build applications that leverage the power of large language models (LLMs) and multi-agent systems. Among these, LangChain, LangGraph, and the Microsoft Agent Framework … Continue reading
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OpenTelemetry in Microsoft Agent Framework Apps
Observability has become a critical component for ensuring the performance and reliability of applications. OpenTelemetry, an open-source observability framework, provides developers with the tools necessary to collect and export telemetry data from their applications. When integrated with the Microsoft Agent … Continue reading
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Agentic Table of Contents (so far)
RAG – A quick example RAG in detail Deeper into RAG The R in RAG PEAS for Agentic AI AI Reasoning and Planning REACT and Agents in AI Creating a multi-agent system (Python & LangChain/LangGraph) part 1 of 6 Migrating … Continue reading
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Limit token usage in Microsoft Agent Framework
In the rapidly evolving landscape of artificial intelligence, managing costs associated with API usage is a critical concern for developers. The Microsoft Agent Framework offers a powerful tool in this regard: ChatClientAgentRunOptions. This component allows developers to cap the number … Continue reading
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Middleware in Microsoft Agent Framework
A critical need, when creating multi-agent applications is to manage token usage in API calls. This is where middleware plays a crucial role. In this post, we will explore what middleware is within the Microsoft Agent Framework, why it is … Continue reading
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Activity Source in Microsoft Agent Framework
In the rapidly evolving landscape of artificial intelligence, the ability to monitor and debug multi-agent systems is paramount. The Microsoft Agent Framework (MAF) has taken a significant step forward by integrating OpenTelemetry, a powerful observability framework that enhances the monitoring … Continue reading
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