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.
Since I don’t know enough about what you can do with local models - I figured this is a great time to start digging into them. Plus, why not learn them with RAG and Semantic Kernel - two things I’ve spent a lot of time with this year. That should give me a good staring point to dig into agents early 2025.
Over the past year I have played with a few local models using Ollama, LMStudio and ONNX but I haven’t created any projects using them yet. This blog series will chronicle my exploration into using local models to implement RAG applications using C# and the good and bad I find along the way … stay tuned!
Blogs in this series (to be updated as they get published):
- … coming soon.
Are you using local models for your RAG? If so, I’d love to hear more about it on twitter/X.
If you have a comment, please message me @haleyjason on twitter/X.