Large Language models are all over the place, driving the advancement of AI in today's era. For enterprises and businesses, integrating LLM with custom data sources is crucial to provide more contextual understanding and reduce hallucinations. In my talk, Tarun will emphasize on building an effective RAG pipeline for production using Open Source LLMs. In simple words, Retrieval Augmented Generation involves retrieving relevant documents as context for user queries and leveraging LLMs to generate more accurate responses.

It is a fully hands-on workshop/session, where participants will construct an entire RAG pipeline using open-source: LLMs, vector databases, and embeddings.