Jason Haley

Ramblings from an Independent Consultant

Wisconsin .NET User Group

Last Thursday night I spoke at the Wisconsin .NET User Group near Milwaukee, WI. I was nice to meet so many .NET developers interested in RAG and AI. To carry on the tradition from my Memphis talk, I gave the presentation a local look using images related to Milwaukee generated from Bing/create. Talk: Getting Started with Retrieval Augmented Generation (RAG) The presentation pdf can be downloaded here. One of my demos failed to deploy before the talk, but I don’t think it was missed due to having so many good questions.

Posted by Jason on Tuesday, August 13, 2024

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

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. Related posts: Study Notes: Graph RAG - Property Graph RAG Study Notes: Graph RAG - Property Graph RAG (The Projects) Where To Get The Code The code for this entry is in my Github repo semantic-kernel-getting-started under the notebooks folder:

Posted by Jason on Tuesday, August 6, 2024

Study Notes: Graph RAG - Property Graph RAG

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. Related posts: Study Notes: Graph RAG - Property Graph RAG (The Notebook) Study Notes: Graph RAG - Property Graph RAG (The Projects) NOTE: My approach to this topic was to find a way to improve a typical RAG implementation that only uses vector similarity searching.

Posted by Jason on Monday, August 5, 2024

Study Notes: Text-to-SQL Code Sample

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.

Posted by Jason on Saturday, July 6, 2024

Study Notes: Text-to-SQL

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.

Posted by Jason on Friday, July 5, 2024

Boston Azure June 2024

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.

Posted by Jason on Tuesday, June 25, 2024

Demo Review: Chat Copilot

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!

Posted by Jason on Tuesday, June 18, 2024

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.

Posted by Jason on Monday, June 10, 2024

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.

Posted by Jason on Monday, May 27, 2024

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.

Posted by Jason on Sunday, May 19, 2024

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ABOUT ME
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Jason is an experienced developer and solutions architect focused on helping companies provide real business value with custom software development using the Microsoft stack of technologies. This includes C#, .NET, Azure and AI services. In 2024, Jason was awarded a Microsoft MVP in AI - highlighting his latest focus on AI and specifically Generative AI technologies in real world business applications. The prior seven years, he was a Microsoft Azure MVP.

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Jason Haley MVP