Jason Haley

Ramblings from an Independent Consultant

Semantic Kernel Hello World WebSearchEnginePlugin

A couple of weeks ago I thought I’d written my last of these blogs, mainly due to me getting more in depth with Semantic Kernel. However, after I watched Will Velida’s video Using Bing Search API in the Semantic Kernel SDK … I couldn’t help but wonder what the API calls were behind the scenes. Will does a great job at explaining how to use the plugin and the Bing resource needed to make calls to the search API, so I won’t get into that part of it - I want to focus on the usefulness and API calls made by the plugin.

Semantic Kernel Hello World Planners Part 2

Last week in the Semantic Kernel Hello World Planners Part 1 entry, I used the Handlebars planner to implement the sample Hello World functionality and then looked at the token difference between using a saved plan vs. generating a plan. In this entry I use the Function Calling Stepwise Planner to create the sample Hello World functionality and compare it to the implementation in the Semantic Kernel Hello World Plugins Part 3 entry.

Semantic Kernel Hello World Planners Part 1

A few weeks ago in the Semantic Kernel Hello World Plugins Part 3 blog entry, I showed how to use OpenAI Function Calling. The last half of that entry was all about how to view the response and request JSON going back and forth to OpenAI, which detailed four API calls. In this entry I look at using the Handlebars Planner to accomplish the same functionality. Then I’ll show the request and response JSON for both using a saved plan as well as having the LLM create a plan and end with a token usage comparison.

Semantic Kernel Hello World Plugins Part 3

Last week I blogged Part 2 showing the creation of a native function plugin, in this post I want to take that native function a step further and use the OpenAI Function calling. This will allow us to not provide the current date when making the call to get a historic daily fact and have OpenAI call a function to get the current date. I’ve added the HelloWorld.Plugin3.Console project to the GitHub repo for the code in this blog entry.

Semantic Kernel Hello World Plugins Part 2

Two weeks ago I blogged Part 1, in which I moved the prompt to a prompt template. In this part, I implement a native function that will take in the current date and make the call to the LLM. I’ve put the code for this blog in the HelloWorld.Plugin2.Console project in the same repo as the other SK entries: semantic-kernel-getting-started. Semantic Kernel Plugin: Native Function There is a good Microsoft Learn module: Give your AI agent skills that walks you through the details of what a native function is and how to implement them.

Semantic Kernel Hello World Plugins Part 1

A couple of weeks ago, in my last entry I created a simple Hello World application with Semantic Kernel. Since then, I’ve worked my way through the MS Learning path: APL-2005 Develop AI agents using Azure OpenAI and the Semantic Kernel SDK - which I highly recommend if you are also learning SK. In this entry I’m going to start with the code from the last entry and extract the prompt to a plugin.

Semantic Kernel Hello World

This past Thursday night after the Virtual Boston Azure meetup, Bill Wilder (@codingoutloud) created an AI mini-workshop (hands on) for the attendees that were interested in getting hands on with code using the Azure OpenAI API. This post is me using the same idea but with Semantic Kernel. OpenAI Chat Hello World C# Bill provided the following code for us to get a simple OpenAI chat working: using Azure; using Azure.

Demo Review: Azure Vector Search AI Assistant

Demo Review: Azure Vector Search AI Assistant This is the fourth C# demo in The RAG Demo Chronicles (Blog Series) and is the first demo so far that saves its history to a database. This Retrieval Augmented Generation (RAG) demo is a little different than the last three because it primarily uses data from a database as the content to search instead of documents. It also uses Semantic Kernel more than other demos have, which is neat to see too.

Demo Review: Azure Search OpenAI Demo C#

Demo Review: Azure Search OpenAI Demo C# If you are looking for Retrieval Augmented Generation (RAG) demos that utilize Azure Search and Azure OpenAI (along with several other supporting Azure services), then there is a set of related demos that do just that in GitHub. This family of RAG demos consists of: azure-search-openai-demo-csharp - written in C#. azure-search-openai-demo - written in python. azure-search-openai-javascript - written in javascript/typescript. azure-search-openai-demo-java - written in java.