Jason Haley

Ramblings from an Independent Consultant

Virtual Boston Azure Lunchtime November 2024

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

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)

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.

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.