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Semantic Kernel Part 4: Agents
Last updated: Tuesday, January 14, 2025
Published in: CODE Magazine: 2025 - Jan/Feb
In "Semantic Kernel Part 4: Agents," Mike Yeager explores the use of agents within Semantic Kernel (SK) to tackle complex tasks by customizing Large Language Models (LLMs). Mike explains that agents function as specialized LLMs with specific capabilities, such as performing calculations or accessing tools like MATLAB, to produce more accurate and specialized outcomes. You'll learn about creating assistant agents for specific use cases, like tax calculation, and chat agents that collaborate to achieve tasks, exemplified through a software development scenario. These agents simplify processes by being modular and pre-configured, allowing developers to build more extensive, manageable systems while treating agents as source code.
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Semantic Kernel Part 3: Advanced Topics
Last updated: Tuesday, January 14, 2025
Published in: CODE Magazine: 2024 - September/October
Mike details the evolution of his team's development of a Copilot system using Microsoft's Semantic Kernel (SK) framework for Large Language Models (LLMs). Initially, Mike describes their hands-on approach to building a Copilot capable of answering legal contract queries by manually injecting relevant data into prompts. However, as the project advanced, the team adopted GPT-4 and automatic function calling, significantly simplifying their code and enhancing functionality. Mike emphasizes the transformative impact of these new technologies, which allowed for more effective and efficient application development with minimal manual intervention.