Introduction
In this video, you'll learn how to build an AI chatbot using Retrieval-Augmented Generation (RAG) systems. We guide you through obtaining data from Expo Docs, generating vector embeddings, storing them in a vector database, and performing similarity searches. Finally, we'll integrate everything into a sleek chat UI for both mobile and web using Expo and Expo Router.
What You Will Learn?
- RAG Systems: Understand the basics of Retrieval-Augmented Generation and how it enhances chatbot capabilities.
- Data Gathering: Learn how to efficiently obtain data from Expo Docs.
- Vector Embeddings: Discover the process of generating vector embeddings for text data.
- Vector Database: Store and manage embeddings in a vector database for quick retrieval.
- Similarity Searches: Implement similarity searches to fetch relevant information for your chatbot.
- Chat UI Design: Build a simple chat user interface using Expo and Expo Router.
Why Watch This Video?
This tutorial is perfect for developers looking to dive into AI and chatbot development. Follow along and create a powerful AI chatbot, adding an impressive project to your portfolio.
Ready to start building? Open the tutorial in a new tab and..
🚀 ..let’s start building!
