In this session, we'll dive into the process of creating AI applications using the LangChain framework and Node.js. You'll learn how to effectively integrate Large Language Models (LLMs) into your projects, and how to use embeddings to vectorize text-based documents. This embeddings will be stored in a vector database, we will use pgvector, a extension for supporting vectors in PostgreSQL, which is crucial for handling similarity search queries for Retrieval-Augmented Generation (RAG) applications.