This workshop is designed for people with no prior knowledge in generative AI, ML, or NLP. We’ll focus on building a chatbot using Python and Large Language Models (LLMs), utilizing the FAQs from DataTalks and club courses as our source of information.

What We’ll Do:

• Extracting FAQs for the Knowledge Base: We’ll begin by extracting all questions and answers from Google Docs to form our knowledge base. This step involves organizing the data in a format suitable for the chatbot.
• Indexing the Knowledge Base: After extraction, we’ll index this information. Indexing allows the chatbot to efficiently search through the knowledge base to find relevant answers.
• Setting Up the Chatbot in a Jupyter Notebook: Our main activity will be setting up and programming the chatbot in a Jupyter notebook. This will include basic Python coding and understanding how to interface with LLMs.
• Integrating LLMs with RAG: We will integrate LLMs using Retrieval-Augmented Generation (RAG) to enable the chatbot to provide accurate answers. RAG will enhance the chatbot’s ability to interpret questions and retrieve the correct information from the knowledge base.