Request for Assistance in Training LLMs Using RAG for Educational Chatbots

[Alisheikhalii]

@jerryjliu,

I hope this message finds you well. My name is Ali Sheikhali, and I am an AI developer. Over the past three months, I have been working on a specialized AI chatbot designed for educational purposes. The chatbot enables students to ask academic questions and receive answers. However, given the nature of some highly specific academic questions, a standalone AI may not always be able to provide accurate responses. To address this, I am interested in implementing a Retrieval-Augmented Generation (RAG) system to train language models such as Llama or Cloud Sonet.

I have a large dataset consisting of lesson-related PDFs and Word documents that include questions from subjects like Mathematics, Physics, and Biology. These documents also contain mathematical formulas, charts, and occasionally tables. To ensure accurate results, I aim to chunk the content of these PDFs and Word files correctly for training purposes.

While researching online, I came across your insightful video on YouTube (regarding "Knowledge Assistants"), where you discussed topics such as "Advanced Data and Retrieval Modules" and "Advanced Single-Agent Query Flows." I found your explanation highly relevant to my project, particularly in terms of effectively processing and structuring PDF content.

To better explain my use case, I have attached a sample from my dataset as an image. I would greatly appreciate your guidance on how to properly train LLMs using my dataset and how to integrate the RAG system into this process. Any advice, resources, or recommendations you can provide would be incredibly valuable for my project.

Thank you very much for your time and assistance. I look forward to your response.

Best regards,
Ali Sheikhali
AI Developer