Building a RAG Pipeline with LangChain and ChromaDB for Email-Based Chat Applications

Learn to build a Retrieval Augmented Generation (RAG) pipeline in this 18-minute tutorial that demonstrates how to chat with your emails using LangChain and ChromaDB. Master the implementation process starting with obtaining Gmail data, understanding ArXiv integration, and setting up essential tools like LangChain, ChromaDB, and GPT4All. Follow along with hands-on demonstrations of email preprocessing, text splitting techniques, vector store creation, and LLM model integration. Discover how to overcome the limitations of Large Language Models by implementing RAG to enable them to access and process information beyond their training data. Gain practical experience through step-by-step guidance on imports, preprocessing, and the final integration of the LLM model with RAG functionality.