Jason Haley

Ramblings from an Independent Consultant

Techbash 2024

This week I presented at the TechBash conference in Pocono Manor, PA. All the resources for the conference are available on the TechBash GitHub repo. Below are links to my presentations specifically. It was great to see companies sending their employees to conferences again. This was my first time at TechBash, and I finally got to meet Alvin Ashcraft in person (the Morning Dew). I also met a bunch of people from the Philly area and around Pennsylvania, but there were attendees from all over-even a couple of guys from Panama!

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

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: Related posts: Study Notes: Graph RAG - Property Graph RAG Study Notes: Graph RAG - Property Graph RAG (The Notebook) NOTE: In order to get the most out of this blog post, you should first read the related two posts.

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.

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:

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.

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.

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.

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.

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!

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.