Semantic Kernel on Jason Haley

Hands-on Boston AgentCon Workshop

info@jasonhaley.com (Jason Haley) — Tue, 30 Sep 2025 00:00:00 +0000

This past Saturday, I held my latest hands on workshop: From Static Files to Smart Agents: Unlocking Document Intelligence at AgentCon Boston. I ended up with around 30 attendees. There was quite a bit of interaction, with some real practical questions being asked about RAG and GenAI applications.

Hand-on-Lab: From Static Files to Smart Agents: Unlocking Document Intelligence

The repository is located at: https://github.com/JasonHaley/agentcon-boston-workshop

What is it?

The end result (which is the “completed” branch of the repo), is a Chainlit application designed to provide four use cases:

Updated Semantic Kernel Blogs and Github Repo

info@jasonhaley.com (Jason Haley) — Mon, 26 May 2025 00:00:00 +0000

This weekend I upgraded the semantic-kernel-getting-started repository to the latest code.

It was mostly to move to .NET 9 (I’d forgotten it was still all .NET 8) and the latest version of the Semantic Kernel libraries. However there were a few things that needed changed:

Planners Were Deprecated

The Planners were deprecated last year (more information here: Semantic Kernel: Package previews, Graduations & Deprecations).

This means the blog posts Semantic Kernel Hello World Planners Part 1 and Semantic Kernel Hello World Planners Part 2 are not longer relevant. I’ve updated those blog posts indicating the deprecation and have removed the code projects from the solution in Github (the code is still there but not loaded with the solution).

Hands-on AI Workshop Jan 2025

info@jasonhaley.com (Jason Haley) — Sat, 01 Feb 2025 00:00:00 +0000

Yesterday Bill Wilder, Juan Pablo Garcia Gonzalez and I had the second Hands-on AI Workshop - this time in Cambridge MA. Like the last time, the goal was to give the attendees a hands on experience using Semantic Kernel. The target audience was .NET developers using Visual Studio Code looking to learn GenAI.

My presentation and labs focused on RAG.

Talk: Retrieval Augmented Generation (RAG)

I made a few small changes since the December workshop, mostly in the part where I discuss chunking.

Introducing: the Local RAG Series (with Semantic Kernel)

info@jasonhaley.com (Jason Haley) — Sun, 22 Dec 2024 00:00:00 +0000

Announcing: The Local RAG Series with Semantic Kernel

This year I’ve spent a lot of time focusing on Retrieval Augmented Generation (RAG) and its related technologies. I’ve also had my eye on agents and plan to focus on them a lot in 2025. From what I’ve seen with my limited work with agents so far is: they can be chatty. This has lead me to believe that agents will really take off once either the price of LLMs available via APIs lower (a lot) or local models become sufficient to use.

A Semantic Kernel Workshop

info@jasonhaley.com (Jason Haley) — Sun, 08 Dec 2024 00:00:00 +0000

Announcing: A Semantic Kernel Workshop

Friday Bill Wilder, Juan Pablo Garcia Gonzalez and I finally were able to make the workshop we’ve been working on for the past couple of months public. We had an in person day long event where we used the content, which was received really well. The attendees had some good questions - giving us some really good ideas on how to improve the content.

Target audience: .NET developers looking to start using Gen AI in their applications

Hands-on AI Workshop Dec 2024

info@jasonhaley.com (Jason Haley) — Sat, 07 Dec 2024 00:00:00 +0000

Yesterday Bill Wilder, Juan Pablo Garcia Gonzalez and I put on a Hands-on AI Workshop in Burlington MA. The goal was to give the attendees hands on experience using Semantic Kernel. The target audience was .NET developers using Visual Studio Code or Visual Studio looking to learn GenAI.

I gave the middle presentations and labs focusing on RAG.

Talk: Retrieval Augmented Generation (RAG)

This was an intro level presentation on what RAG is and the concepts you need to know to create a RAG system. The presentation can be downloaded on the github here

Azure SQL, Entity Framework, Semantic Kernel Hands-on-Lab

info@jasonhaley.com (Jason Haley) — Mon, 25 Nov 2024 00:00:00 +0000

Announcing: Build a RAG App using Semantic Kernel, Entity Framework and Azure SQL DB Hands-on-Lab

A couple of weeks ago after Azure SQL DB announced their public preview of native vector support, I put a hands on lab together to help people get started with the new feature and EF Core extension. Bill Wilder and I did mentioned it in our presentations on December 12 and December 15, but I haven’t had a chance to announce it for those of you who missed our presentations.

Virtual Boston Azure Lunchtime November 2024

info@jasonhaley.com (Jason Haley) — Fri, 15 Nov 2024 00:00:00 +0000

Today at lunchtime Bill Wilder and I spoke at the Virtual Boston Azure meetup. Our talks were based on the same material we presented on Tuesday night, however I introduced eShopSupport as well today.

The recording of the session can be found on the (Lunchtime editions) Boston Azure YouTube channel.

Talk: Add Gen AI to your existing .NET apps with Semantic Kernel & Azure SQL

My part of the presentation PDF can be downloaded here.

Virtual Boston Azure November 2024

info@jasonhaley.com (Jason Haley) — Tue, 12 Nov 2024 00:00:00 +0000

Last night Bill Wilder and I spoke at the Virtual Boston Azure meetup. Our talks were about adding GenAI to .NET applications. My portion was mostly demos that focused on Azure SQL’s new native VECTOR support, Entity Framework Core and Semantic Kernel.

The recording of the session can be found on the Boston Azure YouTube channel.

Talk: Add Gen AI to your existing .NET apps with Semantic Kernel & Azure SQL

The presentation pdf can be downloaded here.

Study Notes: Graph RAG - Property Graph RAG (The Projects)

info@jasonhaley.com (Jason Haley) — Fri, 16 Aug 2024 00:00:00 +0000

Last week I wrote about the notebook I created when I was working out the flow of the property graph RAG implementation. In this entry I will go through the two projects I created to provide some reusable code as well as allow for better experimentation:

NOTE: In order to get the most out of this blog post, you should first read the related two posts.

Study Notes: Graph RAG - Property Graph RAG (The Notebook)

info@jasonhaley.com (Jason Haley) — Tue, 06 Aug 2024 00:00:00 +0000

Monday I posted my notes on this last month’s study topic of property graph RAG, which has the general information I’ve collected. In this entry I want to go through some code I created in a polyglot notebook (ie. a notebook that has C# code instead of python), when I was working through the steps needed for a property graph RAG application.

Where To Get The Code

The code for this entry is in my Github repo semantic-kernel-getting-started under the notebooks folder:

Study Notes: Graph RAG - Property Graph RAG

info@jasonhaley.com (Jason Haley) — Mon, 05 Aug 2024 00:00:00 +0000

This past month I’ve been focusing on Graph RAG. This entry is an attempt to capture some lessons learned and a place to itemize all the resources I’ve found useful.

NOTE: My approach to this topic was to find a way to improve a typical RAG implementation that only uses vector similarity searching.

Study Notes: Text-to-SQL Code Sample

info@jasonhaley.com (Jason Haley) — Sat, 06 Jul 2024 00:00:00 +0000

Yesterday I posted my notes from this week’s study topic of Text-to-SQL, which if you haven’t read it - provides more information and resources about the topic. In this entry I want to walk through a code sample I put together after playing with a few samples this week.

Where To Get The Code

The code for this entry is in my GitHub repo semantic-kernel-getting-started under the samples/demos/Text-to-Sql directory.

Originally I considered making this a review of the NL2SQL code sample, but I ended up needing to make some changes to it, so I just copied over some of their code for my sample - that is why the nl2sql.library project is there (also there is a Nl2Sql folder in the TextToSqlConsole project with some other files from their repo). If you are looking into Text-to-SQL, I highly recommend taking a look at their sample.

Study Notes: Text-to-SQL

info@jasonhaley.com (Jason Haley) — Fri, 05 Jul 2024 00:00:00 +0000

This week I’ve been researching Text-to-SQL (also known as Natural Language to SQL), below are my study notes to compile all the resources I’ve found on the topic to date. There is also a corresponding blog entry that walks through a code example.

NOTE: I am approaching this topic specifically looking at how it can be used to extend usage scenarios in a RAG application.

Background

Text-to-SQL (or Natural Language to SQL) is a pattern where the objective is to have an LLM generate SQL statements for a database using natural language.

Boston Azure June 2024

info@jasonhaley.com (Jason Haley) — Tue, 25 Jun 2024 00:00:00 +0000

Last night was the Season of AI presentation. We started with Bill Wilder presenting the fundamentals of Generative AI and quick introduction to Azure AI Studio, then I finished up with a .NET code walkthrough implement Retrieval Augmented Generation (RAG) using Semantic Kernel.

It was nice to see a lot of regular faces and meet several new people.

Demo Code

The demo code is on my GitHub repo BostonAzure-June2024 under a subdirectory.

Demo Review: Chat Copilot

info@jasonhaley.com (Jason Haley) — Tue, 18 Jun 2024 00:00:00 +0000

Demo Review: Chat Copilot

This is the fifth C# demo in The RAG Demo Chronicles (Blog Series) and has the most extensive use of Semantic Kernel out of all the demos I’ve reviewed.

The use of Retrieval Augmented Generation (RAG) is different with this project than the other demos I’ve reviewed - mainly because RAG is just one of its features.

With this demo, I also took the time to configure the optional authentication so I could play with the MS Graph plugin … and WOW! Just adding the web searcher and MS Graph plugin really make this a powerful demo app. It gives me a lot of ideas for my own projects.

Semantic Kernel Hello World WebSearchEnginePlugin

info@jasonhaley.com (Jason Haley) — Mon, 10 Jun 2024 00:00:00 +0000

UPDATE: The Bing Search APIS are being deprecated. See the announcement for more details: Bing Search APIs retiring on August 11, 2025. I have updated the post and corresponding Github code to use the Brave connector instead.

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 - (Deprecated)

info@jasonhaley.com (Jason Haley) — Mon, 27 May 2024 00:00:00 +0000

UPDATE: Planners have been deprecated. See this Semantic Kernel blog for more detail: Semantic Kernel: Package previews, Graduations & Deprecations

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 - (Deprecated)

info@jasonhaley.com (Jason Haley) — Sun, 19 May 2024 00:00:00 +0000

UPDATE: Planners have been deprecated. See this Semantic Kernel blog for more detail: Semantic Kernel: Package previews, Graduations & Deprecations

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

info@jasonhaley.com (Jason Haley) — Tue, 30 Apr 2024 00:00:00 +0000

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

info@jasonhaley.com (Jason Haley) — Fri, 26 Apr 2024 00:00:00 +0000

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

info@jasonhaley.com (Jason Haley) — Thu, 11 Apr 2024 00:00:00 +0000

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. I’ve put the code for this blog in the same repo as the last entry: semantic-kernel-getting-started

Semantic Kernel Hello World

info@jasonhaley.com (Jason Haley) — Sat, 30 Mar 2024 00:00:00 +0000

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.AI.OpenAI;


string? key = "...";
string? endpoint = "...";
string? deployment = "...";

// output today's date just for fun
Console.WriteLine($"\n----------------- DEBUG INFO -----------------");
var today = DateTime.Now.ToString("MMMM dd");
Console.WriteLine($"Today is {today}");
Console.WriteLine("----------------------------------------------");


var client = new OpenAIClient(new Uri(endpoint), new AzureKeyCredential(key));

// TODO: CHALLENGE 1: does the AI respond accurately to this prompt? How to fix?
var prompt = $"Tell me an interesting fact from world about an event " +
            $"that took place on {today}. " +
            $"Be sure to mention the date in history for context.";

CompletionsOptions completionsOptions = new()
{
    Temperature = 0.7f,
    DeploymentName = deployment,
    Prompts = { prompt },
    MaxTokens = 250,  // PLEASE DON'T MAKE LARGER THAN 250 (but see what happens at 25)
};

Response<Completions> completionsResponse = client.GetCompletions(completionsOptions);

Console.WriteLine($"\nPROMPT: \n\n{prompt}");

int i = 0;
foreach (var choice in completionsResponse.Value.Choices)
{    
    Console.WriteLine($"\nRESPONSE {++i}/{completionsResponse.Value.Choices.Count}:" +
        $"{choice.Text}");
}

Console.WriteLine($"\n----------------- DEBUG INFO -----------------");
Console.WriteLine($"Tokens used: {completionsResponse.Value.Usage.CompletionTokens}/{completionsOptions.MaxTokens}");
Console.WriteLine("----------------------------------------------");

When you run this code (you’ll of course need to add in you own values for the key, endpoint and deployment), you will get a response like this:

Demo Review: Azure Vector Search AI Assistant

info@jasonhaley.com (Jason Haley) — Mon, 26 Feb 2024 00:00:00 +0000

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#

info@jasonhaley.com (Jason Haley) — Wed, 14 Feb 2024 00:00:00 +0000

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.

This post is about #1 above, I will cover #2 and #3 in later posts, but I will leave the Java version to someone else to review.

Semantic Kernel on Jason Haley

Hands-on Boston AgentCon Workshop

Hand-on-Lab: From Static Files to Smart Agents: Unlocking Document Intelligence

What is it?

Updated Semantic Kernel Blogs and Github Repo

Planners Were Deprecated

Hands-on AI Workshop Jan 2025

Talk: Retrieval Augmented Generation (RAG)

Introducing: the Local RAG Series (with Semantic Kernel)

Announcing: The Local RAG Series with Semantic Kernel

A Semantic Kernel Workshop

Announcing: A Semantic Kernel Workshop

Hands-on AI Workshop Dec 2024

Talk: Retrieval Augmented Generation (RAG)

Azure SQL, Entity Framework, Semantic Kernel Hands-on-Lab

Announcing: Build a RAG App using Semantic Kernel, Entity Framework and Azure SQL DB Hands-on-Lab

Virtual Boston Azure Lunchtime November 2024

Talk: Add Gen AI to your existing .NET apps with Semantic Kernel & Azure SQL

Virtual Boston Azure November 2024

Talk: Add Gen AI to your existing .NET apps with Semantic Kernel & Azure SQL

Study Notes: Graph RAG - Property Graph RAG (The Projects)

Related posts:

Study Notes: Graph RAG - Property Graph RAG (The Notebook)

Related posts:

Where To Get The Code

Study Notes: Graph RAG - Property Graph RAG

Related posts:

Study Notes: Text-to-SQL Code Sample

Where To Get The Code

Study Notes: Text-to-SQL

Background

Boston Azure June 2024

Demo Code

Demo Review: Chat Copilot

Demo Review: Chat Copilot

Semantic Kernel Hello World WebSearchEnginePlugin

UPDATE: The Bing Search APIS are being deprecated. See the announcement for more details: Bing Search APIs retiring on August 11, 2025. I have updated the post and corresponding Github code to use the Brave connector instead.

Semantic Kernel Hello World Planners Part 2 - (Deprecated)

UPDATE: Planners have been deprecated. See this Semantic Kernel blog for more detail: Semantic Kernel: Package previews, Graduations & Deprecations

Semantic Kernel Hello World Planners Part 1 - (Deprecated)

UPDATE: Planners have been deprecated. See this Semantic Kernel blog for more detail: Semantic Kernel: Package previews, Graduations & Deprecations

Semantic Kernel Hello World Plugins Part 3

Semantic Kernel Hello World Plugins Part 2

Semantic Kernel Plugin: Native Function

Semantic Kernel Hello World Plugins Part 1

Semantic Kernel Hello World

OpenAI Chat Hello World C#

Demo Review: Azure Vector Search AI Assistant

Demo Review: Azure Vector Search AI Assistant

Demo Review: Azure Search OpenAI Demo C#

Demo Review: Azure Search OpenAI Demo C#

UPDATE: The Bing Search APIS are being deprecated. See the announcement for more details: Bing Search APIs retiring on August 11, 2025. I have updated the post and corresponding Github code to use the Brave connector instead.