Let AI Be Your Docs

Participants need a MongoDB Atlas account, an OpenAI account, and Node.js version 18 or later, along with basic Git knowledge.

AI can take React applications to the next level by making them intelligent, context-aware, and capable of providing real-time data and insights.

The workshop aims to demonstrate how to integrate AI into React applications using technologies like MongoDB, Atlas Search, OpenAI, and LangChain.

The workshop is presented by Jesse Hall, a senior developer advocate at MongoDB, known for his YouTube channel CodeStacker.

AI helps businesses solve real problems, increases productivity, and enhances user engagement and satisfaction by making applications smarter and more context-aware.

The workshop uses Next.js, OpenAI, LangChain, Vercel AI SDK, and MongoDB Atlas Search, including vector search.

MongoDB Atlas is used to store vector embeddings and perform vector search, enabling the application to provide more contextual and meaningful user experiences.

Yes, it is possible to use self-hosted LLMs and MongoDB locally for development, but the vector search functionality is a feature of MongoDB Atlas in the cloud.

Vector search uses embeddings to represent complex, multidimensional data, enabling semantic search to find information that is contextually relevant rather than just keyword-based.

RAG leverages vectors to pull in real-time, contextually relevant data to augment the capabilities of large language models, providing a memory or ground truth to reduce hallucinations.