RAG for college course catelog


I’m currently a university student and my latest project aims to develop an LLM specifically designed to assist students in navigating our university’s course catalog. The goal is to create a tool that is not only cost-effective but also straightforward to maintain and implement, while ensuring it delivers accurate and helpful information.

At present, I’m exploring RAG. I’m very much open to suggestions and insights from the community regarding the best tech stack and architecture to use.

So far, I’ve been considering various tools and frameworks like Flowise AI, Langchain, Pinecone, Colbert. I’m even thinking about using numpy to convert vector embeddings to store in memory every time. If anyone has experience or suggestions about integrating these tools, or if there are other options I should look into, I would greatly appreciate your input.

I’m excited to hear your thoughts and recommendations. This project is an opportunity to create something that could genuinely enhance the educational experience for students like me.

Looking forward to your suggestions and insights!

Hi Seogenis,

I have fond impression with LangChain ReAct agent tools and its RAG tech stack. However, I do not have experience to speak about it. So you may take a bit research into its documentation. If you are comfortable with reading source code, that would be even better:

Though I am experience with Llama Index, Deep Lake Vector Database, and Open AI Agents functional calling tools. I am happy to help, please send me direct message, we can discuss some strategies to implement this project of yours.


Happy learning!

Duy Nguyen