Chat With Your Data using Langchain

You've likely heard of Large Language Models such as LLaMa2 and GPT-4. These are great for general purposes, but what if you want to use these models to ask questions about your own data? That's where Retrieval Augmented Generation (RAG) can help.

In this session, we'll demonstrate how Langchain can streamline your language model workflows, particularly emphasizing the transformative "Chat with your Data" paradigm and vector databases' crucial role in RAG.

We'll cover topics such as integrating vector databases into your workflows, utilizing data embeddings for similarity searches for context injection, and how to use an open-source model from Huggingface to generate intelligent responses to user queries.

Langchain: python.langchain.com
Huggingface: https://huggingface.co/
ChromaDB: https://www.trychroma.com/