LLM Agents at the Edge
The goal of the project will be to create a RAG application that leverages LLMs running at the edge.
This application will be used by students and faculty to quickly find answers to questions related to OSU specific information.
Objectives
Objectives:
- Scrape OSU documentation data
- Organize and enrich scraped data
- Create sentence embedding using data
- Store sentence embedding in a Vector database
- Set up local LLMs
- Create notebooks to implement agent frameworks
- Create a simple RAG workflow
Stretch Goals:
- Create a backend application to host the LLMs
- Create a frontend application with a “chatbot" interface
We will leverage the latest tools and workflows to build this application.
- LangGraph
- LangChain
- HuggingFace transformers
- Open source LLMs
- Vector Databases
- Web scrapers
- Jupyter Notebooks
- AI Agent frameworks
This project will require students to learn about these tools and the workflows that are used.
For more information on these techniques, please see:
Once we have a working prototype, our stretch goals will be to enhance our simple RAG application with more advanced techniques and then bundle that into a frontend chatbot application.
Motivations
As the LLM space is evolving quickly my motivation is to introduce students to the latest technologies and tools to build RAG applications.
With this application, we could provide a tool for students and faculty to leverage that could provide them ways of quickly finding answers to questions related to OSU through a chatbot like interface.
Qualifications
Minimum Qualifications:
None Listed Preferred Qualifications:
None Listed
Details
Project Partner:
Kyle Prouty
NDA/IPA:No Agreement Required
Number Groups:1
Project Status:Accepting Applicants
Keywords:WebData ScienceMachine Learning (ML)Data EngineeringNew Product or Game